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JMSL^TM Numerical Library 5.0.1

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A

abs(Complex) - Static method in class com.imsl.math.Complex: Returns the absolute value (modulus) of a Complex, |z|.
abs(int) - Static method in class com.imsl.math.JMath: Returns the absolute value of an int.
abs(long) - Static method in class com.imsl.math.JMath: Returns the absolute value of a long.
abs(float) - Static method in class com.imsl.math.JMath: Returns the absolute value of a float.
abs(double) - Static method in class com.imsl.math.JMath: Returns the absolute value of a double.
absolute(int) - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the given row number in this ResultSet object.
AbstractChartNode - Class in com.imsl.chart: The base class of all of the nodes in both the 2D and 3D chart trees.
AbstractChartNode(AbstractChartNode) - Constructor for class com.imsl.chart.AbstractChartNode
AbstractFlatFile - Class in com.imsl.io: Reads a text or binary file as a ResultSet.
AbstractFlatFile() - Constructor for class com.imsl.io.AbstractFlatFile: Initializes an AbstractFlatFile.
AbstractFlatFile.FlatFileSQLException - Exception in com.imsl.io: A SQLException thrown by the AbstractFlatFile class.
accrint(GregorianCalendar, GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the interest which has accrued on a security that pays interest periodically.
accrintm(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the interest which has accrued on a security that pays interest at maturity.
acos(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse cosine (arc cosine) of a Complex, with branch cuts outside the interval [-1,1] along the real axis.
acos(double) - Static method in class com.imsl.math.JMath: Returns the inverse (arc) cosine of a double.
acosh(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse hyperbolic cosine (arc cosh) of a Complex, with a branch cut at values less than one along the real axis.
acosh(double) - Static method in class com.imsl.math.Hyperbolic: Returns the inverse hyperbolic cosine of its argument.
Activation - Interface in com.imsl.datamining.neural: Interface implemented by perceptron activation functions.
add(Complex, Complex) - Static method in class com.imsl.math.Complex: Returns the sum of two Complex objects, x+y.
add(Complex, double) - Static method in class com.imsl.math.Complex: Returns the sum of a Complex and a double, x+y.
add(double, Complex) - Static method in class com.imsl.math.Complex: Returns the sum of a double and a Complex, x+y.
add(Complex[][], Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Add two rectangular Complex arrays, a + b.
add(Complex, Complex, ComplexSparseMatrix, ComplexSparseMatrix) - Static method in class com.imsl.math.ComplexSparseMatrix: Performs element-wise addition of two complex sparse matrices A, B of type ComplexSparseMatrix,
add(double[][], double[][]) - Static method in class com.imsl.math.Matrix: Add two rectangular arrays, a + b.
add(Physical, Physical) - Static method in class com.imsl.math.Physical: Add two compatible Physical objects.
add(double, double, SparseMatrix, SparseMatrix) - Static method in class com.imsl.math.SparseMatrix: Performs element-wise addition of two real sparse matrices A, B of type SparseMatrix,
addCenterLine() - Method in class com.imsl.chart.qc.ShewhartControlChart: Adds the center line to the control chart and returns the newly added line.
addControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart: Adds a control limit to the chart.
addCumulativeLine(AxisXY) - Method in class com.imsl.chart.qc.ParetoChart: Adds a cumulative line to the specified axis.
addCumulativeLine() - Method in class com.imsl.chart.qc.ParetoChart: Creates a new right-side axis and adds a cumulative line to it.
addDataMarkers() - Method in class com.imsl.chart.qc.CuSumStatus: Adds the original data to the chart on a newly created axis.
addDataMarkers(AxisXY) - Method in class com.imsl.chart.qc.CuSumStatus: Adds the original data to the chart.
addLegendItem(int, ChartNode) - Method in class com.imsl.chart.Chart: Adds a legend to this ChartNode.
addLowerControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart: Creates lower ControlLimit, adds it to the control chart, and returns the newly created object.
addMouseListener(MouseListener) - Method in class com.imsl.chart.Chart: Adds a MouseListener to the component associated with this chart.
addMouseMotionListener(MouseMotionListener) - Method in class com.imsl.chart.Chart: Adds a MouseMotionListener to the component associated with this chart.
addNode(Node) - Method in class com.imsl.datamining.neural.Layer: Associates a Perceptron with this Layer.
addPickListener(PickListener) - Method in class com.imsl.chart.ChartNode: Adds a PickListener to this node.
addPostRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart: Adds a Paint object to draw to the canvas after the the 3D image is rendered.
addPreRenderPaint(Canvas3DChart.Paint) - Method in class com.imsl.chart3d.Canvas3DChart: Adds a Paint object to draw to the canvas before the the 3D image is rendered.
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AmbientLight
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Axis3D
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisBox
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisLabel
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisLine
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisTitle
addToSceneGraph(Group) - Method in class com.imsl.chart3d.AxisXYZ
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Background
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Chart3D
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ChartLights
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ChartNode3D: Called to add this object to the scene graph.
addToSceneGraph(Group) - Method in class com.imsl.chart3d.ColormapLegend
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Data
addToSceneGraph(Group) - Method in class com.imsl.chart3d.DirectionalLight
addToSceneGraph(Group) - Method in class com.imsl.chart3d.MajorTick
addToSceneGraph(Group) - Method in class com.imsl.chart3d.PointLight
addToSceneGraph(Group) - Method in class com.imsl.chart3d.Surface
addUpperControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart: Creates upper ControlLimit, adds it to the control chart, and returns the newly created object.
addWecoLimits() - Method in class com.imsl.chart.qc.ShewhartControlChart: Adds lines for the Western Electric Company Rules.
ADJUSTED_R_SQUARED_CRITERION - Static variable in class com.imsl.stat.SelectionRegression: Indicates (adjusted ) criterion regression.
AFTER_SUCCESSFUL_STEP - Static variable in class com.imsl.math.OdeRungeKutta: Used by method examineStep to indicate examining after a successful step
AFTER_UNSUCCESSFUL_STEP - Static variable in class com.imsl.math.OdeRungeKutta: Used by method examineStep to indicate examining after an unsuccessful step
afterLast() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the end of this ResultSet object, just after the last row.
ALL - Static variable in class com.imsl.stat.RegressorsForGLM: The n indicator variables are the dummy variables.
allConverged() - Method in class com.imsl.math.ZeroFunction: Returns true if the iterations for all of the roots have converged.
ALPHA_FACTOR_ANALYSIS - Static variable in class com.imsl.stat.FactorAnalysis: Indicates alpha factor analysis.
AmbientLight - Class in com.imsl.chart3d: An ambient light.
AmbientLight(Chart3D) - Constructor for class com.imsl.chart3d.AmbientLight: Creates an ambient light.
amordegrc(double, GregorianCalendar, GregorianCalendar, double, int, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the depreciation for each accounting period.
amorlinc(double, GregorianCalendar, GregorianCalendar, double, int, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the depreciation for each accounting period.
amultp(double[], double[]) - Method in interface com.imsl.math.ConjugateGradient.Function: A user-supplied function which computes z=Ap.
amultp(double[], double[]) - Method in interface com.imsl.math.GenMinRes.Function: Used to compute where A is the matrix of coefficients to solve and p and z are arrays of length n, the order of matrix A.
ANNUAL - Static variable in class com.imsl.finance.Bond: Coupon payments are made annually.
ANOVA - Class in com.imsl.stat: Analysis of Variance table and related statistics.
ANOVA(double[][]) - Constructor for class com.imsl.stat.ANOVA: Analyzes a one-way classification model.
ANOVA(double, double, double, double, double) - Constructor for class com.imsl.stat.ANOVA: Construct an analysis of variance table and related statistics.
ANOVAFactorial - Class in com.imsl.stat: Analyzes a balanced factorial design with fixed effects.
ANOVAFactorial(int, int[], double[]) - Constructor for class com.imsl.stat.ANOVAFactorial: Constructor for ANOVAFactorial.
AR_1 - Static variable in class com.imsl.stat.ARMAEstimateMissing: Indicates that missing values should be estimated using an autoregressive time series with 1 lag.
AR_P - Static variable in class com.imsl.stat.ARMAEstimateMissing: Indicates that missing values should be estimated using an autoregressive time series with a maximum lag of maxLag.
ARAutoUnivariate - Class in com.imsl.stat: Automatically determines the best autoregressive time series model using Akaike's Information Criterion.
ARAutoUnivariate(int, double[]) - Constructor for class com.imsl.stat.ARAutoUnivariate: ARAutoUnivariate constructor.
ARAutoUnivariate.Formatter - Class in com.imsl.stat: Simple formatter for ARAutoUnivariate logging
ARAutoUnivariate.Formatter() - Constructor for class com.imsl.stat.ARAutoUnivariate.Formatter
ARAutoUnivariate.TriangularMatrixSingularException - Exception in com.imsl.stat: The input triangular matrix is singular.
ARAutoUnivariate.TriangularMatrixSingularException(String) - Constructor for exception com.imsl.stat.ARAutoUnivariate.TriangularMatrixSingularException
ARAutoUnivariate.TriangularMatrixSingularException(String, Object[]) - Constructor for exception com.imsl.stat.ARAutoUnivariate.TriangularMatrixSingularException
argument(Complex) - Static method in class com.imsl.math.Complex: Returns the argument (phase) of a Complex, in radians, with a branch cut along the negative real axis.
ARMA - Class in com.imsl.stat: Computes least-square estimates of parameters for an ARMA model.
ARMA(int, int, double[]) - Constructor for class com.imsl.stat.ARMA: Constructor for ARMA.
ARMA.IllConditionedException - Exception in com.imsl.stat: The problem is ill-conditioned.
ARMA.IllConditionedException(String) - Constructor for exception com.imsl.stat.ARMA.IllConditionedException: Constructs an IllConditionedException with the specified detail message.
ARMA.IllConditionedException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.IllConditionedException: Constructs an IllConditionedException with the specified detail message.
ARMA.IncreaseErrRelException - Exception in com.imsl.stat: The bound for the relative error is too small.
ARMA.IncreaseErrRelException(String) - Constructor for exception com.imsl.stat.ARMA.IncreaseErrRelException: Constructs an IncreaseErrRelException with the specified detail message.
ARMA.IncreaseErrRelException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.IncreaseErrRelException: Constructs an IncreaseErrRelException with the specified detail message.
ARMA.MatrixSingularException - Exception in com.imsl.stat: The input matrix is singular.
ARMA.MatrixSingularException(String) - Constructor for exception com.imsl.stat.ARMA.MatrixSingularException: Constructs an MatrixSingularException with the specified detail message.
ARMA.MatrixSingularException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.MatrixSingularException: Constructs an MatrixSingularException with the specified detail message.
ARMA.NewInitialGuessException - Exception in com.imsl.stat: The iteration has not made good progress.
ARMA.NewInitialGuessException(String) - Constructor for exception com.imsl.stat.ARMA.NewInitialGuessException: Constructs an NewInitialGuessException with the specified detail message.
ARMA.NewInitialGuessException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.NewInitialGuessException: Constructs an NewInitialGuessException with the specified detail message.
ARMA.TooManyCallsException - Exception in com.imsl.stat: The number of calls to the function has exceeded the maximum number of iterations times the number of moving average (MA) parameters + 1.
ARMA.TooManyCallsException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyCallsException: Constructs an TooManyCallsException with the specified detail message.
ARMA.TooManyCallsException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyCallsException: Constructs an TooManyCallsException with the specified detail message.
ARMA.TooManyFcnEvalException - Exception in com.imsl.stat: Maximum number of function evaluations exceeded.
ARMA.TooManyFcnEvalException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyFcnEvalException: Constructs an TooManyFcnEvalException with the specified detail message.
ARMA.TooManyFcnEvalException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyFcnEvalException: Constructs an TooManyFcnEvalException with the specified detail message.
ARMA.TooManyITNException - Exception in com.imsl.stat: Maximum number of iterations exceeded.
ARMA.TooManyITNException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyITNException: Constructs an TooManyITNException with the specified detail message.
ARMA.TooManyITNException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyITNException
ARMA.TooManyJacobianEvalException - Exception in com.imsl.stat: Maximum number of Jacobian evaluations exceeded.
ARMA.TooManyJacobianEvalException(String) - Constructor for exception com.imsl.stat.ARMA.TooManyJacobianEvalException: Constructs an TooManyJacobianEvalException with the specified detail message.
ARMA.TooManyJacobianEvalException(String, Object[]) - Constructor for exception com.imsl.stat.ARMA.TooManyJacobianEvalException: Constructs an TooManyJacobianEvalException with the specified detail message.
ARMAEstimateMissing - Class in com.imsl.stat: Estimates missing values in a time series collected with equal spacing.
ARMAEstimateMissing(int[], double[]) - Constructor for class com.imsl.stat.ARMAEstimateMissing: Constructor for ARMAEstimateMissing.
ARMAMaxLikelihood - Class in com.imsl.stat: Computes maximum likelihood estimates of parameters for an ARMA model with p and q autoregressive and moving average terms respectively.
ARMAMaxLikelihood(int, int, double[]) - Constructor for class com.imsl.stat.ARMAMaxLikelihood: Constructor for ARMAMaxLikelihood.
ARMAMaxLikelihood.InitialMAException - Exception in com.imsl.stat: The initial values for the moving average parameters are not invertible.
ARMAMaxLikelihood.InitialMAException(String) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.InitialMAException: Constructs an InitialMAException with the specified detail message.
ARMAMaxLikelihood.InitialMAException(String, Object[]) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.InitialMAException: Constructs an InitialMAException with the specified detail message.
ARMAMaxLikelihood.NonInvertibleException - Exception in com.imsl.stat: The solution is noninvertible.
ARMAMaxLikelihood.NonInvertibleException(String) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonInvertibleException: Constructs a NonInvertible exception with the specified detail message.
ARMAMaxLikelihood.NonInvertibleException(String, Object[]) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonInvertibleException: Constructs a NonInvertibleException exception with the specified detail message.
ARMAMaxLikelihood.NonStationaryException - Exception in com.imsl.stat: The solution is nonstationary.
ARMAMaxLikelihood.NonStationaryException(String) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonStationaryException: Constructs a NonStationary exception with the specified detail message.
ARMAMaxLikelihood.NonStationaryException(String, Object[]) - Constructor for exception com.imsl.stat.ARMAMaxLikelihood.NonStationaryException: Constructs a NonStationary exception with the specified detail message.
ARSeasonalFit - Class in com.imsl.stat: Estimates the optimum seasonality parameters for a time series using an autoregressive model, AR(p), to represent the time series.
ARSeasonalFit(int, int[][], double[]) - Constructor for class com.imsl.stat.ARSeasonalFit: Constructor for ARSeasonalFit.
ascending(int[]) - Static method in class com.imsl.stat.Sort: Function to sort an integer array into ascending order.
ascending(int[], int[]) - Static method in class com.imsl.stat.Sort: Sort an integer array into ascending order and returns the permutation vector.
ascending(double[]) - Static method in class com.imsl.stat.Sort: Sort an array into ascending order.
ascending(double[], int[]) - Static method in class com.imsl.stat.Sort: Sort an array into ascending order and returns the permutation vector.
ascending(double[][], int) - Static method in class com.imsl.stat.Sort: Sort a matrix into ascending order by the first nkeys.
ascending(double[][], int[]) - Static method in class com.imsl.stat.Sort: Sort a matrix into ascending order by specified keys.
ascending(double[][], int, int[]) - Static method in class com.imsl.stat.Sort: Sort an array into ascending order by the first nkeys and returns the permutation vector.
ascending(double[][], int[], int[]) - Static method in class com.imsl.stat.Sort: Sort a matrix into ascending order by specified keys and returns the permutation vector.
asin(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse sine (arc sine) of a Complex, with branch cuts outside the interval [-1,1] along the real axis.
asin(double) - Static method in class com.imsl.math.JMath: Returns the inverse (arc) sine of a double.
asinh(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse hyperbolic sine (arc sinh) of a Complex, with branch cuts outside the interval [-i,i].
asinh(double) - Static method in class com.imsl.math.Hyperbolic: Returns the inverse hyperbolic sine of its argument.
AT_BEGINNING_OF_PERIOD - Static variable in class com.imsl.finance.Finance: Flag used to indicate that payment is made at the beginning of each period.
AT_END_OF_PERIOD - Static variable in class com.imsl.finance.Finance: Flag used to indicate that payment is made at the end of each period.
atan(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse tangent (arc tangent) of a Complex, with branch cuts outside the interval [-i,i] along the imaginary axis.
atan(double) - Static method in class com.imsl.math.JMath: Returns the inverse (arc) tangent of a double.
atan2(double, double) - Static method in class com.imsl.math.JMath: Returns the angle corresponding to a Cartesian point.
atanh(Complex) - Static method in class com.imsl.math.Complex: Returns the inverse hyperbolic tangent (arc tanh) of a Complex, with branch cuts outside the interval [-1,1] on the real axis.
atanh(double) - Static method in class com.imsl.math.Hyperbolic: Returns the inverse hyperbolic tangent of its argument.
AutoCorrelation - Class in com.imsl.stat: Computes the sample autocorrelation function of a stationary time series.
AutoCorrelation(double[], int) - Constructor for class com.imsl.stat.AutoCorrelation: Constructor to compute the sample autocorrelation function of a stationary time series.
AutoCorrelation.NonPosVariancesException - Exception in com.imsl.stat: The problem is ill-conditioned.
AutoCorrelation.NonPosVariancesException(String) - Constructor for exception com.imsl.stat.AutoCorrelation.NonPosVariancesException: Constructs an NonPosVariancesException with the specified detail message.
AutoCorrelation.NonPosVariancesException(String, Object[]) - Constructor for exception com.imsl.stat.AutoCorrelation.NonPosVariancesException: Constructs an NonPosVariancesException with the specified detail message.
AUTOSCALE_DATA - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that autoscaling is to be done by scanning the data nodes.
AUTOSCALE_DENSITY - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that autoscaling is to adjust the "Density" attribute.
AUTOSCALE_NUMBER - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that autoscaling is to adjust the "Number" attribute.
AUTOSCALE_OFF - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that autoscaling is turned off.
AUTOSCALE_WINDOW - Static variable in class com.imsl.chart.AbstractChartNode: Flag used to indicate that autoscaling is to be done by using the "Window" attribute.
Axis - Class in com.imsl.chart: The Axis node provides the mapping for all of its children from the user coordinate space to the device (screen) space.
Axis(Chart) - Constructor for class com.imsl.chart.Axis: Contructs an Axis node.
Axis1D - Class in com.imsl.chart: An x-axis or a y-axis.
Axis3D - Class in com.imsl.chart3d: An x-axis, y-axis or a z-axis.
AXIS_TITLE_AT_END - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "AxisTitlePosition" indicating that the axis title should be placed at the end of the axis.
AXIS_TITLE_PARALLEL - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "AxisTitlePosition" indicating that the axis title should be placed parallel to the axis.
AXIS_X - Static variable in class com.imsl.chart.AbstractChartNode: Flag to indicate x-axis.
AXIS_X_TOP - Static variable in class com.imsl.chart.ChartNode: Flag to indicate x-axis placed on top of the chart.
AXIS_Y - Static variable in class com.imsl.chart.AbstractChartNode: Flag to indicate y-axis.
AXIS_Y_RIGHT - Static variable in class com.imsl.chart.ChartNode: Flag to indicate y-axis placed to the right of the chart.
AXIS_Z - Static variable in class com.imsl.chart.AbstractChartNode: Flag to indicate z-axis.
AxisBox - Class in com.imsl.chart3d: Box behind the axis.
AxisLabel - Class in com.imsl.chart: The labels on an axis.
AxisLabel - Class in com.imsl.chart3d: The labels on an axis.
AxisLine - Class in com.imsl.chart: The axis line.
AxisLine - Class in com.imsl.chart3d: The axis line.
AxisR - Class in com.imsl.chart: The R-axis in a polar plot.
AxisRLabel - Class in com.imsl.chart: The labels on an axis.
AxisRLine - Class in com.imsl.chart: The radius axis line in a polar plot.
AxisRMajorTick - Class in com.imsl.chart: The major tick marks for the radius axis in a polar plot.
AxisTheta - Class in com.imsl.chart: The angular axis in a polar plot.
AxisTitle - Class in com.imsl.chart: The title on an axis.
AxisTitle - Class in com.imsl.chart3d: Axis title.
AxisUnit - Class in com.imsl.chart: The unit title on an axis.
AxisXY - Class in com.imsl.chart: The axes for an x-y chart.
AxisXY(Chart) - Constructor for class com.imsl.chart.AxisXY: Create an AxisXY.
AxisXYZ - Class in com.imsl.chart3d: The axes for an x-y-z chart.
AxisXYZ(Chart3D) - Constructor for class com.imsl.chart3d.AxisXYZ: Create an AxisXYZ.

B

Background - Class in com.imsl.chart: The background of a chart.
Background - Class in com.imsl.chart3d: Background of the chart.
backward(Complex[]) - Method in class com.imsl.math.ComplexFFT: Compute the complex periodic sequence from its Fourier coefficients.
backward(double[]) - Method in class com.imsl.math.FFT: Compute the real periodic sequence from its Fourier coefficients.
BACKWARD_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression: Indicates backward regression.
Bar - Class in com.imsl.chart: A bar chart.
Bar(AxisXY) - Constructor for class com.imsl.chart.Bar: Constructs a bar chart.
Bar(AxisXY, double[]) - Constructor for class com.imsl.chart.Bar: Constructs a simple bar chart using supplied y data.
Bar(AxisXY, double[], double[]) - Constructor for class com.imsl.chart.Bar: Constructs a simple bar chart using supplied x and y data.
Bar(AxisXY, double[][]) - Constructor for class com.imsl.chart.Bar: Constructs a grouped bar chart using supplied x and y data.
Bar(AxisXY, double[], double[][]) - Constructor for class com.imsl.chart.Bar: Constructs a grouped bar chart using supplied x and y data.
Bar(AxisXY, double[][][]) - Constructor for class com.imsl.chart.Bar: Constructs a stacked, grouped bar chart using supplied y data.
Bar(AxisXY, double[], double[][][]) - Constructor for class com.imsl.chart.Bar: Constructs a stacked, grouped bar chart using supplied x and y data.
BAR_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.ChartNode: Flag to indicate a horizontal bar chart.
BAR_TYPE_VERTICAL - Static variable in class com.imsl.chart.ChartNode: Flag to indicate a vertical bar chart.
BarItem - Class in com.imsl.chart: A single bar in a bar chart.
BarSet - Class in com.imsl.chart: A set of bars in a bar chart.
BARTLETTS_FORMULA - Static variable in class com.imsl.stat.AutoCorrelation: Indicates standard error computation using Bartlett's formula.
BARTLETTS_FORMULA - Static variable in class com.imsl.stat.CrossCorrelation: Indicates standard error computation using Bartlett's formula.
BARTLETTS_FORMULA_NOCC - Static variable in class com.imsl.stat.CrossCorrelation: Indicates standard error computation using Bartlett's formula with the assumption of no cross-correlation.
basis(int, double) - Method in interface com.imsl.stat.RegressionBasis: Public interface for the nonlinear least-squares function.
Basis30e360 - Static variable in class com.imsl.finance.DayCountBasis: Computations based on the assumption of 30 days per month and 360 days per year.
BasisActual360 - Static variable in class com.imsl.finance.DayCountBasis: Computations are based on the number of days in a month based on the actual calendar value and the number of days, but assuming 360 days per year.
BasisActual365 - Static variable in class com.imsl.finance.DayCountBasis: Computations are based on the number of days in a month based on the actual calendar value and the number of days, but assuming 365 days per year.
BasisActualActual - Static variable in class com.imsl.finance.DayCountBasis: Computations are based on the actual calendar.
BasisNASD - Static variable in class com.imsl.finance.DayCountBasis: Computations based on the assumption of 30 days per month and 360 days per year.
BasisPart - Interface in com.imsl.finance: Component of DayCountBasis.
BasisPart30E360 - Static variable in class com.imsl.finance.DayCountBasis: Computations based on the assumption of 30 days per month and 360 days per year.
BasisPart365 - Static variable in class com.imsl.finance.DayCountBasis: Computations based on the assumption of 365 days per year.
BasisPartActual - Static variable in class com.imsl.finance.DayCountBasis: Computations are based on the actual calendar.
BasisPartNASD - Static variable in class com.imsl.finance.DayCountBasis: Computations based on the assumption of 30 days per month and 360 days per year.
BEFORE_STEP - Static variable in class com.imsl.math.OdeRungeKutta: Used by method examineStep to indicate examining before the next step
beforeFirst() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the front of this ResultSet object, just before the first row.
BEGIN_COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a column label is to be returned.
BEGIN_COLUMN_LABELS - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for beginning a column label row is to be returned.
BEGIN_ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatted string for beginning an entry is to be returned.
BEGIN_MATRIX - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for beginning a matrix is to be returned.
BEGIN_ROW - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for beginning a row is to be returned.
BEGIN_ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for beginning a row label is to be returned.
beginGet() - Method in class com.imsl.io.AbstractFlatFile: This method should be called at the start of every getType method.
Bessel - Class in com.imsl.math: Collection of Bessel functions.
beta(double, double) - Static method in class com.imsl.math.Sfun: Returns the value of the Beta function.
beta(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the beta cumulative probability distribution function.
betaIncomplete(double, double, double) - Static method in class com.imsl.math.Sfun: Returns the incomplete Beta function ratio.
betaMean(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the mean of the beta cumulative probability distribution function
betaProb(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the beta probability density function.
betaVariance(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the variance of the beta cumulative probability distribution function
BINARY_VARIABLE - Static variable in class com.imsl.io.MPSReader: Variable must be either 0 or 1.
BinaryClassification - Class in com.imsl.datamining.neural: Classifies patterns into two classes.
BinaryClassification(Network) - Constructor for class com.imsl.datamining.neural.BinaryClassification: Creates a binary classifier.
binomial(int, int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the binomial cumulative probability distribution function.
binomialProb(int, int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the binomial probability density function.
bivariateNormal(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the bivariate normal cumulative probability distribution function.
BLUE - Static variable in interface com.imsl.chart.Colormap: Linear blue colormap.
BLUE_GREEN_RED_YELLOW - Static variable in interface com.imsl.chart.Colormap: Blue/green/red/yellow colormap.
BLUE_RED - Static variable in interface com.imsl.chart.Colormap: Blue/red colormap.
BLUE_WHITE - Static variable in interface com.imsl.chart.Colormap: Blue/white colormap.
Bond - Class in com.imsl.finance: Collection of bond functions.
Bond() - Constructor for class com.imsl.finance.Bond
BOUNDED_SCALING - Static variable in class com.imsl.datamining.neural.ScaleFilter: Flag to indicate bounded scaling.
BOUNDED_Z_SCORE_SCALING_MEAN_STDEV - Static variable in class com.imsl.datamining.neural.ScaleFilter: Flag to indicate bounded z-score scaling using the mean and standard deviation.
BOUNDED_Z_SCORE_SCALING_MEDIAN_MAD - Static variable in class com.imsl.datamining.neural.ScaleFilter: Flag to indicate bounded z-score scaling using the median and mean absolute difference.
BoundedLeastSquares - Class in com.imsl.math: Solves a nonlinear least-squares problem subject to bounds on the variables using a modified Levenberg-Marquardt algorithm.
BoundedLeastSquares(BoundedLeastSquares.Function, int, int, int, double[], double[]) - Constructor for class com.imsl.math.BoundedLeastSquares: Constructor for BoundedLeastSquares.
BoundedLeastSquares.FalseConvergenceException - Exception in com.imsl.math: False convergence - The iterates appear to be converging to a noncritical point.
BoundedLeastSquares.FalseConvergenceException(String) - Constructor for exception com.imsl.math.BoundedLeastSquares.FalseConvergenceException: Constructs an FalseConvergenceException with the specified detail message.
BoundedLeastSquares.FalseConvergenceException(String, Object[]) - Constructor for exception com.imsl.math.BoundedLeastSquares.FalseConvergenceException: Constructs an FalseConvergenceException with the specified detail message.
BoundedLeastSquares.Function - Interface in com.imsl.math: Public interface for the user-supplied function to evaluate the function that defines the least-squares problem.
BoundedLeastSquares.Jacobian - Interface in com.imsl.math: Public interface for the user-supplied function to compute the Jacobian.
BoxPlot - Class in com.imsl.chart: Draws a multiple-group Box plot.
BoxPlot(AxisXY, double[], double[][]) - Constructor for class com.imsl.chart.BoxPlot: Constructs a box plot chart node with specified x values.
BoxPlot(AxisXY, double[], BoxPlot.Statistics[]) - Constructor for class com.imsl.chart.BoxPlot: Constructs a box plot chart node with specified x values.
BoxPlot(AxisXY, double[][]) - Constructor for class com.imsl.chart.BoxPlot: Constructs a box plot chart.
BoxPlot.Statistics - Class in com.imsl.chart: Computes the statistics for one set of observations in a Boxplot.
BoxPlot.Statistics(double[]) - Constructor for class com.imsl.chart.BoxPlot.Statistics: Creates a new instance of BoxPlot.Statistics.
BOXPLOT_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.BoxPlot: Value for attribute "BoxPlotType" indicating that this is a horizontal box plot.
BOXPLOT_TYPE_VERTICAL - Static variable in class com.imsl.chart.BoxPlot: Value for attribute "BoxPlotType" indicating that this is a horizontal box plot.
breakPoint - Variable in class com.imsl.math.Spline: The breakpoint array of length n, where n is the number of piecewise polynomials.
BsInterpolate - Class in com.imsl.math: Extension of the BSpline class to interpolate data points.
BsInterpolate(double[], double[]) - Constructor for class com.imsl.math.BsInterpolate: Constructs a B-spline that interpolates the given data points.
BsInterpolate(double[], double[], int) - Constructor for class com.imsl.math.BsInterpolate: Constructs a B-spline that interpolates the given data points and order, using a default "not-a-knot" spline knot sequence.
BsInterpolate(double[], double[], int, double[]) - Constructor for class com.imsl.math.BsInterpolate: Constructs a B-spline that interpolates the given data points, using the specified order and knots.
BsLeastSquares - Class in com.imsl.math: Extension of the BSpline class to compute a least squares spline approximation to data points.
BsLeastSquares(double[], double[], int) - Constructor for class com.imsl.math.BsLeastSquares: Constructs a least squares B-spline approximation to the given data points.
BsLeastSquares(double[], double[], int, int) - Constructor for class com.imsl.math.BsLeastSquares: Constructs a least squares B-spline approximation to the given data points.
BsLeastSquares(double[], double[], int, int, double[], double[]) - Constructor for class com.imsl.math.BsLeastSquares: Constructs a least squares B-spline approximation to the given data points.
BSpline - Class in com.imsl.math: BSpline represents and evaluates univariate B-splines.
BSpline() - Constructor for class com.imsl.math.BSpline
BufferedPaint - Class in com.imsl.chart3d: A Paint object cached into an image.
BufferedPaint(Canvas3DChart.Paint, int, int, int, int, Component) - Constructor for class com.imsl.chart3d.BufferedPaint: The paint method in Canvas3DChart.Paint is written into an image of size width by height.
BW_LINEAR - Static variable in interface com.imsl.chart.Colormap: Black and white (grayscale) colormap.
byteValue() - Method in class com.imsl.math.Complex: Returns the value of the real part as a byte.

C

cancelRowUpdates() - Method in class com.imsl.io.AbstractFlatFile: Cancels the updates made to the current row in this ResultSet object.
Candlestick - Class in com.imsl.chart: Candlestick plot of stock data.
Candlestick(AxisXY, Date, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.Candlestick: Constructs a candlestick chart node beginning with specified start date.
Candlestick(AxisXY, double[], double[], double[], double[], double[]) - Constructor for class com.imsl.chart.Candlestick: Constructs a candlestick chart node at specified axis points.
CandlestickItem - Class in com.imsl.chart: A candlestick for the up days or the down days.
Canvas3DChart - Class in com.imsl.chart3d: A canvas for rendering a 3D chart.
Canvas3DChart() - Constructor for class com.imsl.chart3d.Canvas3DChart: Creates a Canvas3DChart with a new Chart3D object.
Canvas3DChart(Chart3D) - Constructor for class com.imsl.chart3d.Canvas3DChart: Creates a Canvas3DChart with a given Chart3D object.
Canvas3DChart.Paint - Interface in com.imsl.chart3d: Interface for 2D drawing on the canvas before or after the the 3D image is drawn.
capabilityIndexCp(double, double) - Method in class com.imsl.chart.qc.XbarR: Returns the capability index
$c_p=frac{mathrm{USL}-mathrm{LSL}}{6sigma}$
capabilityIndexCp(double, double) - Method in class com.imsl.chart.qc.XbarS: Returns the capability index
$c_p=frac{mathrm{USL}-mathrm{LSL}}{6sigma}$
capabilityIndexCpk(double, double) - Method in class com.imsl.chart.qc.XbarR: Returns the capability index $c_{pk}$
$c_{pk}=minleft[frac{mathrm{USL}-bar{x}}{3sigma},frac{bar{x}-mathrm{LSL}}{3sigma}right]$
capabilityIndexCpk(double, double) - Method in class com.imsl.chart.qc.XbarS: Returns the capability index $c_{pk}$
$c_{pk}=minleft[frac{mathrm{USL}-bar{x}}{3sigma},frac{bar{x}-mathrm{LSL}}{3sigma}right]$
CategoricalGenLinModel - Class in com.imsl.stat: Analyzes categorical data using logistic, probit, Poisson, and other linear models.
CategoricalGenLinModel(double[][], int) - Constructor for class com.imsl.stat.CategoricalGenLinModel: Constructs a new CategoricalGenLinModel.
CategoricalGenLinModel.ClassificationVariableException - Exception in com.imsl.stat: The ClassificationVariable vector has not been initialized.
CategoricalGenLinModel.ClassificationVariableException() - Constructor for exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableException: Constructs a ClassificationVariableException.
CategoricalGenLinModel.ClassificationVariableLimitException - Exception in com.imsl.stat: The Classification Variable limit set by the user through setUpperBound has been exceeded.
CategoricalGenLinModel.ClassificationVariableLimitException(int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableLimitException: Constructs a ClassificationVariableLimitException.
CategoricalGenLinModel.ClassificationVariableValueException - Exception in com.imsl.stat: The number of distinct values for each Classification Variable must be greater than 1.
CategoricalGenLinModel.ClassificationVariableValueException(int, int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.ClassificationVariableValueException: Constructs a ClassificationVariableValueException.
CategoricalGenLinModel.DeleteObservationsException - Exception in com.imsl.stat: The number of observations to be deleted (set by setObservationMax) has grown too large.
CategoricalGenLinModel.DeleteObservationsException(int) - Constructor for exception com.imsl.stat.CategoricalGenLinModel.DeleteObservationsException: Constructs a DeleteObservationsException.
CChart - Class in com.imsl.chart.qc: CChart is a c-chart for monitoring the count of the number of defects when defects are rare.
CChart(AxisXY, int[]) - Constructor for class com.imsl.chart.qc.CChart: Creates a C-chart given the number of defects in a series of samples.
Cdf - Class in com.imsl.stat: Cumulative probability distribution functions, probability density functions, and their inverses.
cdf(double) - Method in interface com.imsl.stat.CdfFunction: Public interface for the user-supplied cumulative distribution function to be used by InverseCdf.
CdfFunction - Interface in com.imsl.stat: Public interface for the user-supplied cumulative distribution function to be used by InverseCdf and ChiSquaredTest.
ceil(double) - Static method in class com.imsl.math.JMath: Returns the value of a double rounded toward positive infinity to an integral value.
CENTER_MEAN - Static variable in class com.imsl.stat.ARSeasonalFit: Indicates the transformed series should be centered using the average of the differenced series.
CENTER_MEDIAN - Static variable in class com.imsl.stat.ARSeasonalFit: Indicates the transformed series should be centered using the median of the differenced series.
Chart - Class in com.imsl.chart: The root node of the chart tree.
Chart() - Constructor for class com.imsl.chart.Chart: This is the root of our tree, it has no parent.
Chart(Component) - Constructor for class com.imsl.chart.Chart: This is the root of our tree, it has no parent.
Chart(Image) - Constructor for class com.imsl.chart.Chart: This is the root of our tree, it has no parent.
chart - Variable in class com.imsl.chart.JPanelChart: The embedded chart.
Chart3D - Class in com.imsl.chart3d: Root node of a 3d chart tree.
Chart3D() - Constructor for class com.imsl.chart3d.Chart3D: Creates a new instance of Chart3D
ChartFunction - Interface in com.imsl.chart: An interface that allows a function to be plotted.
ChartLights - Class in com.imsl.chart3d: Default set of lights.
ChartNode - Class in com.imsl.chart: The base class of all of the nodes in the 2D chart tree.
ChartNode(ChartNode) - Constructor for class com.imsl.chart.ChartNode: Construct a ChartNode object.
ChartNode3D - Class in com.imsl.chart3d: The base class of all of the nodes in the 3D chart tree.
ChartNode3D(ChartNode3D) - Constructor for class com.imsl.chart3d.ChartNode3D: Construct a ChartNode3D object.
ChartServlet - Class in com.imsl.chart: The base class for chart servlets.
ChartServlet() - Constructor for class com.imsl.chart.ChartServlet
ChartSpline - Class in com.imsl.chart: Wrap a spline into a ChartFunction to be plotted.
ChartSpline(Spline) - Constructor for class com.imsl.chart.ChartSpline: Creates a ChartSpline from a Spline.
ChartSpline(Spline, int) - Constructor for class com.imsl.chart.ChartSpline: Creates a ChartSpline from the derivative of a Spline.
ChartTitle - Class in com.imsl.chart: The main title of a chart.
ChartXML - Class in com.imsl.chart.xml: Create a Chart from an XML file.
ChartXML(String) - Constructor for class com.imsl.chart.xml.ChartXML: Creates a ChartXML from an XML file.
ChartXML(String, boolean) - Constructor for class com.imsl.chart.xml.ChartXML: Creates a ChartXML from an XML file.
ChartXML(InputSource, boolean) - Constructor for class com.imsl.chart.xml.ChartXML: Creates a ChartXML from an XML source.
ChartXML(Document) - Constructor for class com.imsl.chart.xml.ChartXML: Creates a ChartXML from a DOM tree.
check(int) - Method in class com.imsl.chart.Draw
checkCompatibility(Physical, Physical) - Static method in class com.imsl.math.Physical: Checks the compatibility of two Physical objects.
checkerboard(int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a checkerboard pattern.
checkMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Check that all of the rows in the Complex matrix have the same length.
checkMatrix(double[][]) - Static method in class com.imsl.math.Matrix: Check that all of the rows in the matrix have the same length.
checkSquareMatrix(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Check that the Complex matrix is square.
checkSquareMatrix() - Method in class com.imsl.math.ComplexSparseMatrix: Check that the matrix is square.
checkSquareMatrix(double[][]) - Static method in class com.imsl.math.Matrix: Check that the matrix is square.
checkSquareMatrix() - Method in class com.imsl.math.SparseMatrix: Check that the matrix is square.
chi(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the chi-squared cumulative probability distribution function.
chiMean(double) - Static method in class com.imsl.stat.Cdf: Evaluates the mean of the chi-squared cumulative probability distribution function
chiProb(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the chi-squared probability density function
ChiSquaredTest - Class in com.imsl.stat: Chi-squared goodness-of-fit test.
ChiSquaredTest(CdfFunction, double[], int) - Constructor for class com.imsl.stat.ChiSquaredTest: Constructor for the Chi-squared goodness-of-fit test.
ChiSquaredTest(CdfFunction, int, int) - Constructor for class com.imsl.stat.ChiSquaredTest: Constructor for the Chi-squared goodness-of-fit test
ChiSquaredTest(int) - Method in class com.imsl.stat.NormalityTest: Performs the chi-squared goodness-of-fit test.
ChiSquaredTest.DidNotConvergeException - Exception in com.imsl.stat: The iteration did not converge
ChiSquaredTest.DidNotConvergeException(String) - Constructor for exception com.imsl.stat.ChiSquaredTest.DidNotConvergeException
ChiSquaredTest.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.stat.ChiSquaredTest.DidNotConvergeException
ChiSquaredTest.NoObservationsException - Exception in com.imsl.stat: There are no observations.
ChiSquaredTest.NoObservationsException(String, Object[]) - Constructor for exception com.imsl.stat.ChiSquaredTest.NoObservationsException
ChiSquaredTest.NotCDFException - Exception in com.imsl.stat: The function is not a Cumulative Distribution Function (CDF).
ChiSquaredTest.NotCDFException(String, Object[]) - Constructor for exception com.imsl.stat.ChiSquaredTest.NotCDFException
chiVariance(double) - Static method in class com.imsl.stat.Cdf: Evaluates the variance of the chi-squared cumulative probability distribution function
Cholesky - Class in com.imsl.math: Cholesky factorization of a matrix of type double.
Cholesky(double[][]) - Constructor for class com.imsl.math.Cholesky: Create the Cholesky factorization of a symmetric positive definite matrix of type double.
Cholesky.NotSPDException - Exception in com.imsl.math: The matrix is not symmetric, positive definite.
Cholesky.NotSPDException() - Constructor for exception com.imsl.math.Cholesky.NotSPDException
circle(int, int, int) - Method in class com.imsl.chart.DrawMap: Sets a circle as the target.
cleanup() - Method in class com.imsl.chart3d.Chart3D: Cleanup memory use and references used by the chart.
clearWarnings() - Method in class com.imsl.io.AbstractFlatFile: Clears all warnings reported on this ResultSet object.
clone(Map) - Method in class com.imsl.chart.AbstractChartNode: Returns a deep-copy clone of this node.
clone(Object, Map) - Method in class com.imsl.chart.AbstractChartNode: Returns a deep copy of an Object.
clone(Map, Map) - Method in class com.imsl.chart.AbstractChartNode: Returns a deep copy of a Hashtable.
clone(List, Map) - Method in class com.imsl.chart.AbstractChartNode: Returns a deep copy of a vector of ChartNode's.
clone() - Method in class com.imsl.chart.Chart: Returns a clone of the graphics tree.
clone(Map) - Method in class com.imsl.chart.Chart: Returns a clone of this node.
clone() - Method in class com.imsl.chart3d.BufferedPaint
clone() - Method in class com.imsl.chart3d.Chart3D: Returns a clone of the graphics tree.
clone(Map) - Method in class com.imsl.chart3d.Chart3D: Returns a clone of this node.
clone() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Clones a copy of the trainer.
clone() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Clones a copy of the trainer.
clone() - Method in class com.imsl.math.DenseLP: Creates and returns a copy of this object.
clone() - Method in class com.imsl.stat.FaureSequence: Returns a copy of this object.
clone() - Method in class com.imsl.stat.MersenneTwister: Returns a clone of this object.
clone() - Method in class com.imsl.stat.MersenneTwister64: Returns a clone of this object.
close() - Method in class com.imsl.io.AbstractFlatFile: Releases this ResultSet object's database and JDBC resources immediately instead of waiting for this to happen when it is automatically closed.
ClusterHierarchical - Class in com.imsl.stat: Performs a hierarchical cluster analysis from a distance matrix.
ClusterHierarchical(double[][], int, int) - Constructor for class com.imsl.stat.ClusterHierarchical: Constructor for ClusterHierarchical.
ClusterKMeans - Class in com.imsl.stat: Perform a K-means (centroid) cluster analysis.
ClusterKMeans(double[][], double[][]) - Constructor for class com.imsl.stat.ClusterKMeans: Constructor for ClusterKMeans.
ClusterKMeans.ClusterNoPointsException - Exception in com.imsl.stat: There is a cluster with no points
ClusterKMeans.ClusterNoPointsException(String) - Constructor for exception com.imsl.stat.ClusterKMeans.ClusterNoPointsException
ClusterKMeans.ClusterNoPointsException(String, Object[]) - Constructor for exception com.imsl.stat.ClusterKMeans.ClusterNoPointsException
ClusterKMeans.NoConvergenceException - Exception in com.imsl.stat: Convergence did not occur within the maximum number of iterations.
ClusterKMeans.NoConvergenceException(String) - Constructor for exception com.imsl.stat.ClusterKMeans.NoConvergenceException
ClusterKMeans.NoConvergenceException(String, Object[]) - Constructor for exception com.imsl.stat.ClusterKMeans.NoConvergenceException
ClusterKMeans.NonnegativeFreqException - Exception in com.imsl.stat: Frequencies must be nonnegative.
ClusterKMeans.NonnegativeFreqException(String) - Constructor for exception com.imsl.stat.ClusterKMeans.NonnegativeFreqException
ClusterKMeans.NonnegativeFreqException(String, Object[]) - Constructor for exception com.imsl.stat.ClusterKMeans.NonnegativeFreqException
ClusterKMeans.NonnegativeWeightException - Exception in com.imsl.stat: Weights must be nonnegative.
ClusterKMeans.NonnegativeWeightException(String) - Constructor for exception com.imsl.stat.ClusterKMeans.NonnegativeWeightException
ClusterKMeans.NonnegativeWeightException(String, Object[]) - Constructor for exception com.imsl.stat.ClusterKMeans.NonnegativeWeightException
coef - Variable in class com.imsl.math.BSpline: The B-spline coefficient array.
coef - Variable in class com.imsl.math.Spline: Coefficients of the piecewise polynomials.
color(double) - Method in interface com.imsl.chart.Colormap: Maps the parameterization interval [0,1] into Colors.
color(double, double, double) - Method in interface com.imsl.chart3d.ColorFunction
ColorFunction - Interface in com.imsl.chart3d: Interface to define value dependent colors.
Colormap - Interface in com.imsl.chart: Colormaps are mappings from the unit interval to Colors.
ColormapLegend - Class in com.imsl.chart3d: Adds a legend for a Colormap gradient to the background of the canvas.
ColormapLegend(Chart3D, Colormap, double[]) - Constructor for class com.imsl.chart3d.ColormapLegend: Creates a legend for a Colormap and adds it to the canvas.
ColormapLegend(Chart3D, Colormap, double, double) - Constructor for class com.imsl.chart3d.ColormapLegend
COLUMN_APPROXIMATE_MINIMUM_DEGREE - Static variable in class com.imsl.math.ComplexSuperLU: For column ordering, use column approximate minimum degree ordering.
COLUMN_APPROXIMATE_MINIMUM_DEGREE - Static variable in class com.imsl.math.SuperLU: For column ordering, use column approximate minimum degree ordering.
COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatted string for a given column label is to be returned.
COLUMN_SCALING - Static variable in class com.imsl.math.ComplexSuperLU: Indicates that input matrix A was column scaled before factorization.
COLUMN_SCALING - Static variable in class com.imsl.math.SuperLU: Indicates that input matrix A was column scaled before factorization.
com.imsl - package com.imsl
com.imsl.chart - package com.imsl.chart
com.imsl.chart.qc - package com.imsl.chart.qc
com.imsl.chart.xml - package com.imsl.chart.xml
com.imsl.chart3d - package com.imsl.chart3d
com.imsl.datamining.neural - package com.imsl.datamining.neural
com.imsl.finance - package com.imsl.finance
com.imsl.io - package com.imsl.io
com.imsl.math - package com.imsl.math
com.imsl.stat - package com.imsl.stat
compareTo(Object) - Method in class com.imsl.math.Complex: Compares this Complex to another Object.
compareTo(Complex) - Method in class com.imsl.math.Complex: Compares two Complex objects.
complementaryChi(double, double) - Static method in class com.imsl.stat.Cdf: Calculates the complement of the chi-squared distribution.
complementaryF(double, double, double) - Static method in class com.imsl.stat.Cdf: Calculates the complement of the F distribution function.
complementaryStudentsT(double, double) - Static method in class com.imsl.stat.Cdf: Calculates the complement of the Student's t distribution.
Complex - Class in com.imsl.math: Set of mathematical functions for complex numbers.
Complex(Complex) - Constructor for class com.imsl.math.Complex: Constructs a Complex equal to the argument.
Complex(double, double) - Constructor for class com.imsl.math.Complex: Constructs a Complex with real and imaginary parts given by the input arguments.
Complex(double) - Constructor for class com.imsl.math.Complex: Constructs a Complex with a zero imaginary part.
Complex() - Constructor for class com.imsl.math.Complex: Constructs a Complex equal to zero.
ComplexFFT - Class in com.imsl.math: Complex FFT.
ComplexFFT(int) - Constructor for class com.imsl.math.ComplexFFT: Constructs a complex FFT object.
ComplexLU - Class in com.imsl.math: LU factorization of a matrix of type Complex.
ComplexLU(Complex[][]) - Constructor for class com.imsl.math.ComplexLU: Creates the LU factorization of a square matrix of type Complex.
ComplexMatrix - Class in com.imsl.math: Complex matrix manipulation functions.
ComplexSparseCholesky - Class in com.imsl.math: Sparse Cholesky factorization of a matrix of type ComplexSparseMatrix.
ComplexSparseCholesky(ComplexSparseMatrix) - Constructor for class com.imsl.math.ComplexSparseCholesky: Constructs the matrix structure for the Cholesky factorization of a sparse Hermitian positive definite matrix of type ComplexSparseMatrix.
ComplexSparseCholesky.NotSPDException - Exception in com.imsl.math: The matrix is not Hermitian, positive definite.
ComplexSparseCholesky.NotSPDException() - Constructor for exception com.imsl.math.ComplexSparseCholesky.NotSPDException
ComplexSparseCholesky.NumericFactor - Class in com.imsl.math: Data structures and functions for the numeric Cholesky factor.
ComplexSparseCholesky.SymbolicFactor - Class in com.imsl.math: Data structures and functions for the symbolic Cholesky factor.
ComplexSparseMatrix - Class in com.imsl.math: Sparse matrix of type Complex.
ComplexSparseMatrix(int, int) - Constructor for class com.imsl.math.ComplexSparseMatrix: Creates a new instance of ComplexSparseMatrix.
ComplexSparseMatrix(ComplexSparseMatrix) - Constructor for class com.imsl.math.ComplexSparseMatrix: Creates a new instance of ComplexSparseMatrix which is a copy of another ComplexSparseMatrix.
ComplexSparseMatrix(ComplexSparseMatrix.SparseArray) - Constructor for class com.imsl.math.ComplexSparseMatrix: Constructs a complex sparse matrix from a SparseArray object.
ComplexSparseMatrix(int, int, int[][], Complex[][]) - Constructor for class com.imsl.math.ComplexSparseMatrix: Constructs a sparse matrix from SparseArray (Java Sparse Array) data.
ComplexSparseMatrix.SparseArray - Class in com.imsl.math: The SparseArray class uses public fields to hold the data for a sparse matrix in the Java Sparse Array format.
ComplexSparseMatrix.SparseArray() - Constructor for class com.imsl.math.ComplexSparseMatrix.SparseArray
ComplexSuperLU - Class in com.imsl.math: Computes the LU factorization of a general sparse matrix of type ComplexSparseMatrix by a column method and solves a sparse linear system of equations .
ComplexSuperLU(ComplexSparseMatrix) - Constructor for class com.imsl.math.ComplexSuperLU: Constructor for ComplexSuperLU.
compute(double[], double[]) - Method in interface com.imsl.math.BoundedLeastSquares.Function: Public interface for the user-supplied function to evaluate the function that defines the least-squares problem.
compute(double[], double[]) - Method in interface com.imsl.math.BoundedLeastSquares.Jacobian: Public interface for the user-supplied function to compute the Jacobian.
compute() - Method in class com.imsl.stat.ANOVAFactorial: Analyzes a balanced factorial design with fixed effects.
compute() - Method in class com.imsl.stat.ARAutoUnivariate: Determines the autoregressive model with the minimum AIC by fitting autoregressive models from 0 to maxlag lags using the method of moments or an estimation method specified by the user through setEstimationMethod.
compute() - Method in class com.imsl.stat.ARMA: Computes least-square estimates of parameters for an ARMA model.
compute() - Method in class com.imsl.stat.ARMAMaxLikelihood: Computes the exact maximum likelihood estimates for the autoregressive and moving average parameters of an ARMA time series
compute() - Method in class com.imsl.stat.ARSeasonalFit: Computes the minimum AIC and optimum values for s and d based upon the candidates provided in sInitial and dInitial, and computes the values for the transformed series, .
compute() - Method in class com.imsl.stat.ClusterKMeans: Computes the cluster means.
compute(int) - Method in class com.imsl.stat.Covariances: Computes the matrix.
compute(double[], int[]) - Method in class com.imsl.stat.Difference: Computes a Difference series.
compute() - Method in class com.imsl.stat.GARCH: Computes estimates of the parameters of a GARCH(p,q) model.
compute() - Static method in class com.imsl.stat.KaplanMeierECDF: Computes the empirical CDF
compute() - Method in class com.imsl.stat.MultipleComparisons: Performs Student-Newman-Keuls multiple comparisons test.
compute(double[][], double[]) - Method in class com.imsl.stat.SelectionRegression: Computes the best multiple linear regression models.
compute(double[][], double[], double[]) - Method in class com.imsl.stat.SelectionRegression: Computes the best weighted multiple linear regression models.
compute(double[][], double[], double[], double[]) - Method in class com.imsl.stat.SelectionRegression: Computes the best weighted multiple linear regression models using frequencies for each observation.
compute(double[][], int) - Method in class com.imsl.stat.SelectionRegression: Computes the best multiple linear regression models using a user-supplied covariance matrix.
compute() - Method in class com.imsl.stat.SignTest: Performs a sign test.
compute() - Method in class com.imsl.stat.StepwiseRegression: Builds the multiple linear regression models using forward selection, backward selection, or stepwise selection.
compute() - Method in class com.imsl.stat.WilcoxonRankSum: Performs a Wilcoxon rank sum test.
computeLags(int[], int[], double[]) - Method in class com.imsl.datamining.neural.TimeSeriesClassFilter: Computes lags of an array sorted first by class designations and then descending chronological order.
computeLags(int, double[][]) - Method in class com.imsl.datamining.neural.TimeSeriesFilter: Lags time series data to a format used for input to a neural network.
computeMin(MinUncon.Function) - Method in class com.imsl.math.MinUncon: Return the minimum of a smooth function of a single variable of type double using function values only or using function values and derivatives.
computeMin(MinUnconMultiVar.Function) - Method in class com.imsl.math.MinUnconMultiVar: Return the minimum point of a function of n variables of type double using a finite-difference gradient or using a user-supplied gradient.
computeRoots(double[]) - Method in class com.imsl.math.ZeroPolynomial: Computes the roots of the polynomial with real coefficients.
computeRoots(Complex[]) - Method in class com.imsl.math.ZeroPolynomial: Computes the roots of the polynomial with Complex coefficients.
computeStatistics(double[][], int[]) - Method in class com.imsl.datamining.neural.BinaryClassification: Computes the classification error statistics for the supplied network patterns and their associated classifications.
computeStatistics(double[][], int[]) - Method in class com.imsl.datamining.neural.MultiClassification: Computes classification statistics for the supplied network patterns and their associated classifications.
computeStatistics(double[][], double[][]) - Method in class com.imsl.datamining.neural.Network: Computes error statistics.
computeZeros(ZeroFunction.Function, double[]) - Method in class com.imsl.math.ZeroFunction: Returns the zeros of a univariate function.
condition(Complex[][]) - Method in class com.imsl.math.ComplexLU: Return an estimate of the reciprocal of the L1 condition number.
condition(double[][]) - Method in class com.imsl.math.LU: Return an estimate of the reciprocal of the L1 condition number of a matrix.
confidenceMean(double) - Method in class com.imsl.stat.Summary: Returns the confidence interval for the mean (assuming normality).
confidenceVariance(double) - Method in class com.imsl.stat.Summary: Returns the confidence interval for the variance (assuming normality).
conjugate(Complex) - Static method in class com.imsl.math.Complex: Returns the complex conjugate of a Complex object.
ConjugateGradient - Class in com.imsl.math: Solves a real symmetric definite linear system using the conjugate gradient method with optional preconditioning.
ConjugateGradient(int, ConjugateGradient.Function) - Constructor for class com.imsl.math.ConjugateGradient: Conjugate gradient constructor.
ConjugateGradient.Function - Interface in com.imsl.math: Public interface for the user supplied function to ConjugateGradient.
ConjugateGradient.NoConvergenceException - Exception in com.imsl.math: The conjugate gradient method did not converge within the allowed maximum number of iterations.
ConjugateGradient.NoConvergenceException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NoConvergenceException
ConjugateGradient.NoConvergenceException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NoConvergenceException
ConjugateGradient.NotDefiniteAMatrixException - Exception in com.imsl.math: The input matrix A is indefinite, that is the matrix is not positive or negative definite.
ConjugateGradient.NotDefiniteAMatrixException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteAMatrixException
ConjugateGradient.NotDefiniteAMatrixException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteAMatrixException
ConjugateGradient.NotDefiniteJacobiPreconditionerException - Exception in com.imsl.math: The Jacobi preconditioner is not strictly positive or negative definite.
ConjugateGradient.NotDefiniteJacobiPreconditionerException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteJacobiPreconditionerException
ConjugateGradient.NotDefiniteJacobiPreconditionerException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefiniteJacobiPreconditionerException
ConjugateGradient.NotDefinitePreconditionMatrixException - Exception in com.imsl.math: The Precondition matrix is indefinite.
ConjugateGradient.NotDefinitePreconditionMatrixException(String) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefinitePreconditionMatrixException
ConjugateGradient.NotDefinitePreconditionMatrixException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.NotDefinitePreconditionMatrixException
ConjugateGradient.Preconditioner - Interface in com.imsl.math: Public interface for the user supplied function to ConjugateGradient used for preconditioning.
ConjugateGradient.SingularPreconditionMatrixException - Exception in com.imsl.math: The Precondition matrix is singular.
ConjugateGradient.SingularPreconditionMatrixException(String) - Constructor for exception com.imsl.math.ConjugateGradient.SingularPreconditionMatrixException
ConjugateGradient.SingularPreconditionMatrixException(String, Object[]) - Constructor for exception com.imsl.math.ConjugateGradient.SingularPreconditionMatrixException
conjugateTranspose() - Method in class com.imsl.math.ComplexSparseMatrix: Returns the conjugate transpose of the matrix.
constant(String) - Static method in class com.imsl.math.Physical: Returns the value of a constant, given its name.
constant(String, String) - Static method in class com.imsl.math.Physical: Returns the value of a constant, given its name, in the specified units.
ContingencyTable - Class in com.imsl.stat: Performs a chi-squared analysis of a two-way contingency table.
ContingencyTable(double[][]) - Constructor for class com.imsl.stat.ContingencyTable: Constructs and performs a chi-squared analysis of a two-way contingency table.
CONTINUOUS_VARIABLE - Static variable in class com.imsl.io.MPSReader: Variable is a real number.
Contour - Class in com.imsl.chart: A Contour chart shows level curves of a two-dimensional function.
Contour(AxisXY, double[], double[], double[][], double[]) - Constructor for class com.imsl.chart.Contour: Create a Contour chart from rectangularly gridded data.
Contour(AxisXY, double[], double[], double[][]) - Constructor for class com.imsl.chart.Contour: Create a Contour chart from rectangularly gridded data with computed contour levels.
Contour(AxisXY, double[], double[], double[]) - Constructor for class com.imsl.chart.Contour: Create a Contour chart from scattered data with computed contour levels.
Contour(AxisXY, double[], double[], double[], double[], int) - Constructor for class com.imsl.chart.Contour: Create a Contour chart from scattered data.
Contour.Legend - Class in com.imsl.chart: A legend for a contour chart.
ContourLevel - Class in com.imsl.chart: ContourLevel draws a level curve line and the fill area between the level curve and the next smaller level curve.
ControlLimit - Class in com.imsl.chart.qc: ControlLimit is a control limit line on a process control chart.
convert(Physical, String) - Static method in class com.imsl.math.Physical: Converts a value to a different set of units.
convexity(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the convexity for a security.
copy() - Method in class com.imsl.chart.Chart: Copy the chart to the clipboard.
copyAndSortData(double[], double[]) - Method in class com.imsl.math.Spline: Copy and sort xData into breakPoint and yData into the first column of coef.
copyAndSortData(double[], double[], double[]) - Method in class com.imsl.math.Spline: Copy and sort xData into breakPoint and yData into the first column of coef.
copysign(double, double) - Static method in class com.imsl.math.IEEE: Returns a value with the magnitude of x and with the sign bit of y.
CORRECTED_SSCP_MATRIX - Static variable in class com.imsl.stat.Covariances: Indicates corrected sums of squares and crossproducts matrix.
CORRELATION_MATRIX - Static variable in class com.imsl.stat.Covariances: Indicates correlation matrix.
CORRELATION_MATRIX - Static variable in class com.imsl.stat.FactorAnalysis: Indicates correlation matrix.
cos(Complex) - Static method in class com.imsl.math.Complex: Returns the cosine of a Complex.
cos(double) - Static method in class com.imsl.math.JMath: Returns the cosine of a double.
cosh(Complex) - Static method in class com.imsl.math.Complex: Returns the hyperbolic cosh of a Complex.
cosh(double) - Static method in class com.imsl.math.Hyperbolic: Returns the hyperbolic cosine of its argument.
cot(double) - Static method in class com.imsl.math.Sfun: Returns the cotangent of a double.
countTokens() - Method in class com.imsl.io.Tokenizer: Returns the number of times that the nextToken method can be called without generating an exception.
coupdaybs(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the number of days starting with the beginning of the coupon period and ending with the settlement date.
coupdays(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the number of days in the coupon period containing the settlement date.
coupdaysnc(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the number of days starting with the settlement date and ending with the next coupon date.
coupncd(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the first coupon date which follows the settlement date.
coupnum(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the number of coupons payable between the settlement date and the maturity date.
couppcd(GregorianCalendar, GregorianCalendar, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the coupon date which immediately precedes the settlement date.
Covariances - Class in com.imsl.stat: Computes the sample variance-covariance or correlation matrix.
Covariances(double[][]) - Constructor for class com.imsl.stat.Covariances: Constructor for Covariances.
Covariances.DiffObsDeletedException - Exception in com.imsl.stat: Different observations are being deleted from return matrix than were originally entered.
Covariances.DiffObsDeletedException(String) - Constructor for exception com.imsl.stat.Covariances.DiffObsDeletedException
Covariances.DiffObsDeletedException(String, Object[]) - Constructor for exception com.imsl.stat.Covariances.DiffObsDeletedException
Covariances.MoreObsDelThanEnteredException - Exception in com.imsl.stat: More observations are being deleted from the output covariance matrix than were originally entered (the corresponding row, column of the incidence matrix is less than zero).
Covariances.MoreObsDelThanEnteredException(String) - Constructor for exception com.imsl.stat.Covariances.MoreObsDelThanEnteredException
Covariances.MoreObsDelThanEnteredException(String, Object[]) - Constructor for exception com.imsl.stat.Covariances.MoreObsDelThanEnteredException
Covariances.NonnegativeFreqException - Exception in com.imsl.stat: Frequencies must be nonnegative.
Covariances.NonnegativeFreqException(String) - Constructor for exception com.imsl.stat.Covariances.NonnegativeFreqException
Covariances.NonnegativeFreqException(String, Object[]) - Constructor for exception com.imsl.stat.Covariances.NonnegativeFreqException
Covariances.NonnegativeWeightException - Exception in com.imsl.stat: Weights must be nonnegative.
Covariances.NonnegativeWeightException(String) - Constructor for exception com.imsl.stat.Covariances.NonnegativeWeightException
Covariances.NonnegativeWeightException(String, Object[]) - Constructor for exception com.imsl.stat.Covariances.NonnegativeWeightException
Covariances.TooManyObsDeletedException - Exception in com.imsl.stat: More observations have been deleted than were originally entered (the sum of frequencies has become negative).
Covariances.TooManyObsDeletedException(String) - Constructor for exception com.imsl.stat.Covariances.TooManyObsDeletedException
Covariances.TooManyObsDeletedException(String, Object[]) - Constructor for exception com.imsl.stat.Covariances.TooManyObsDeletedException
createCharts(Chart, double[][]) - Static method in class com.imsl.chart.qc.XbarR: Creates a combined XbarR chart and RChart from data.
createCharts(Chart, int, double[], double[]) - Static method in class com.imsl.chart.qc.XbarR: Creates a combined XbarR chart and RChart given the means and ranges for a series of equally sized samples.
createCharts(Chart, int[], double[], double[]) - Static method in class com.imsl.chart.qc.XbarR: Creates a combined XbarR chart and RChart given the means and ranges for a series of unequally sized samples.
createCharts(Chart, double[][]) - Static method in class com.imsl.chart.qc.XbarS: Creates a combined XbarS chart and SChart from data.
createCharts(Chart, int, double[], double[]) - Static method in class com.imsl.chart.qc.XbarS: Creates a combined XbarS chart and SChart given the means and in sample standard deviations for a series of equally sized samples.
createCharts(Chart, int[], double[], double[]) - Static method in class com.imsl.chart.qc.XbarS: Creates a combined X-bar chart and S-chart given the means and in sample standard deviations for a series of unequally sized samples.
createCumulativeLineAxis() - Method in class com.imsl.chart.qc.ParetoChart: Creates a new axis to hold a cumulative line.
createCustomMarker() - Method in interface com.imsl.chart3d.Data.CustomMarkerFactory: Returns a custom marker.
createDataAxis() - Method in class com.imsl.chart.qc.CuSumStatus: Creates a new axis to hold a cummulative line.
createHiddenLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Creates a HiddenLayer.
createHiddenLayer() - Method in class com.imsl.datamining.neural.Network: Creates the next HiddenLayer in the Network.
createInput() - Method in class com.imsl.datamining.neural.InputLayer: Creates an InputNode in the InputLayer of the neural network.
createInputs(int) - Method in class com.imsl.datamining.neural.InputLayer: Creates a number of InputNodes in this Layer of the neural network.
createPerceptron(Activation, double) - Method in class com.imsl.datamining.neural.HiddenLayer: Creates a Perceptron in this Layer with a specified activation function and bias.
createPerceptron() - Method in class com.imsl.datamining.neural.HiddenLayer: Creates a Perceptron in this Layer of the neural network.
createPerceptron(Activation, double) - Method in class com.imsl.datamining.neural.OutputLayer: Creates a Perceptron in this Layer with a specified Activation and bias.
createPerceptron() - Method in class com.imsl.datamining.neural.OutputLayer: Creates a Perceptron in this Layer of the neural network.
createPerceptrons(int) - Method in class com.imsl.datamining.neural.HiddenLayer: Creates a number of Perceptrons in this Layer of the neural network.
createPerceptrons(int, Activation, double) - Method in class com.imsl.datamining.neural.HiddenLayer: Creates a number of Perceptrons in this Layer with the specified bias.
createPerceptrons(int) - Method in class com.imsl.datamining.neural.OutputLayer: Creates a number of Perceptrons in this Layer of the neural network.
createPerceptrons(int, Activation, double) - Method in class com.imsl.datamining.neural.OutputLayer: Creates a number of Perceptrons in this Layer with specified activation and bias.
CrossCorrelation - Class in com.imsl.stat: Computes the sample cross-correlation function of two stationary time series.
CrossCorrelation(double[], double[], int) - Constructor for class com.imsl.stat.CrossCorrelation: Constructor to compute the sample cross-correlation function of two stationary time series.
CrossCorrelation.NonPosVariancesException - Exception in com.imsl.stat: The problem is ill-conditioned.
CrossCorrelation.NonPosVariancesException(String) - Constructor for exception com.imsl.stat.CrossCorrelation.NonPosVariancesException
CrossCorrelation.NonPosVariancesException(String, Object[]) - Constructor for exception com.imsl.stat.CrossCorrelation.NonPosVariancesException
crosshatch(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a horizonal and vertical crosshatch pattern.
CsAkima - Class in com.imsl.math: Extension of the Spline class to handle the Akima cubic spline.
CsAkima(double[], double[]) - Constructor for class com.imsl.math.CsAkima: Constructs the Akima cubic spline interpolant to the given data points.
CsInterpolate - Class in com.imsl.math: Extension of the Spline class to interpolate data points.
CsInterpolate(double[], double[]) - Constructor for class com.imsl.math.CsInterpolate: Constructs a cubic spline that interpolates the given data points.
CsInterpolate(double[], double[], int, double, int, double) - Constructor for class com.imsl.math.CsInterpolate: Constructs a cubic spline that interpolates the given data points with specified derivative endpoint conditions.
CsPeriodic - Class in com.imsl.math: Extension of the Spline class to interpolate data points with periodic boundary conditions.
CsPeriodic(double[], double[]) - Constructor for class com.imsl.math.CsPeriodic: Constructs a cubic spline that interpolates the given data points with periodic boundary conditions.
CsShape - Class in com.imsl.math: Extension of the Spline class to interpolate data points consistent with the concavity of the data.
CsShape(double[], double[]) - Constructor for class com.imsl.math.CsShape: Construct a cubic spline interpolant which is consistent with the concavity of the data.
CsShape.TooManyIterationsException - Exception in com.imsl.math: Too many iterations.
CsShape.TooManyIterationsException() - Constructor for exception com.imsl.math.CsShape.TooManyIterationsException
CsShape.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.CsShape.TooManyIterationsException
CsShape.TooManyIterationsException(Object[]) - Constructor for exception com.imsl.math.CsShape.TooManyIterationsException
CsSmooth - Class in com.imsl.math: Extension of the Spline class to construct a smooth cubic spline from noisy data points.
CsSmooth(double[], double[]) - Constructor for class com.imsl.math.CsSmooth: Constructs a smooth cubic spline from noisy data using cross-validation to estimate the smoothing parameter.
CsSmooth(double[], double[], double[]) - Constructor for class com.imsl.math.CsSmooth: Constructs a smooth cubic spline from noisy data using cross-validation to estimate the smoothing parameter.
CsSmoothC2 - Class in com.imsl.math: Extension of the Spline class used to construct a spline for noisy data points using an alternate method.
CsSmoothC2(double[], double[], double) - Constructor for class com.imsl.math.CsSmoothC2: Constructs a smooth cubic spline from noisy data using an algorithm based on Reinsch (1967).
CsSmoothC2(double[], double[], double[], double) - Constructor for class com.imsl.math.CsSmoothC2: Constructs a smooth cubic spline from noisy data using an algorithm based on Reinsch (1967) with weights supplied by the user.
CUBIC_SPLINE - Static variable in class com.imsl.stat.ARMAEstimateMissing: Indicates that missing values should be estimated using cublic spline interpolation.
cumipmt(double, int, double, int, int, int) - Static method in class com.imsl.finance.Finance: Returns the cumulative interest paid between two periods.
cumprinc(double, int, double, int, int, int) - Static method in class com.imsl.finance.Finance: Returns the cumulative principal paid between two periods.
CURRENT - Static variable in class com.imsl.math.Physical
currentType - Variable in class com.imsl.chart.Draw
CuSum - Class in com.imsl.chart.qc: CuSum is a cumulative sum chart.
CuSum(AxisXY, double[]) - Constructor for class com.imsl.chart.qc.CuSum: Creates a CuSum chart given the means of a series of samples.
CuSumStatus - Class in com.imsl.chart.qc: CuSumStatus is a cumulative sum status chart.
CuSumStatus(AxisXY, double[], double, double) - Constructor for class com.imsl.chart.qc.CuSumStatus: Creates a CuSumStatus chart.

D

d2 - Static variable in class com.imsl.chart.qc.ShewhartControlChart: This field contains $d_{2,n}$ the mean of the ranges of n samples from a Gaussian distribution.
d3 - Static variable in class com.imsl.chart.qc.ShewhartControlChart: This field contains $d_{3,n}$ the standard deviation of the ranges of n samples from a Gaussian distribution.
DASH_PATTERN_DASH - Static variable in class com.imsl.chart.ChartNode: Flag to draw a dashed line.
DASH_PATTERN_DASH_DOT - Static variable in class com.imsl.chart.ChartNode: Flag to draw a dash-dot pattern line.
DASH_PATTERN_DOT - Static variable in class com.imsl.chart.ChartNode: Flag to draw a dotted line.
DASH_PATTERN_SOLID - Static variable in class com.imsl.chart.ChartNode: Flag to draw solid line.
Data - Class in com.imsl.chart: Draws a data node.
Data(ChartNode) - Constructor for class com.imsl.chart.Data: Creates a data node.
Data(ChartNode, double[]) - Constructor for class com.imsl.chart.Data: Creates a data node with y values.
Data(ChartNode, ChartFunction, double, double) - Constructor for class com.imsl.chart.Data: Creates a data node with y values.
Data(ChartNode, double[], double[]) - Constructor for class com.imsl.chart.Data: Creates a data node with x and y values.
Data - Class in com.imsl.chart3d: Draws a 3D data node.
Data(AxisXYZ) - Constructor for class com.imsl.chart3d.Data: Creates a data node.
Data(AxisXYZ, double[], double[], double[]) - Constructor for class com.imsl.chart3d.Data: Creates a data node with x, y and z values.
Data.CustomMarkerFactory - Interface in com.imsl.chart3d: Factory to create customized markers.
DATA_TYPE_ERROR_X - Static variable in class com.imsl.chart.ErrorBar: Value for attribute "DataType" indicating that this is a horizontal error bar.
DATA_TYPE_ERROR_Y - Static variable in class com.imsl.chart.ErrorBar: Value for attribute "DataType" indicating that this is a vertical error bar.
DATA_TYPE_FILL - Static variable in class com.imsl.chart.ChartNode: Value for attribute "DataType" indicating that the area between the lines connecting the data points and the horizontal reference line (y = attribute "Reference") should be filled.
DATA_TYPE_LINE - Static variable in class com.imsl.chart.ChartNode: Value for attribute "DataType" indicating that the data points should be connected with line segments.
DATA_TYPE_LINE - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "DataType" indicating that the data points should be connected with line segments.
DATA_TYPE_MARKER - Static variable in class com.imsl.chart.ChartNode: Value for attribute "DataType" indicating that a marker should be drawn at each data point.
DATA_TYPE_MARKER - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "DataType" indicating that a marker should be drawn at each data point.
DATA_TYPE_PICTURE - Static variable in class com.imsl.chart.ChartNode: Value for attribute "DataType" indicating that an image (attribute "Image") should be drawn at each data point.
DATA_TYPE_PICTURE - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "DataType" indicating that an image (attribute "Image") should be drawn at each data point.
DATA_TYPE_TUBE - Static variable in class com.imsl.chart.ChartNode: Value for attribute "DataType" indicating that an a tube connecting the data points should be drawn.
DATA_TYPE_TUBE - Static variable in class com.imsl.chart3d.ChartNode3D: Value for attribute "DataType" indicating that a tube connecting the data points should be drawn.
dataRange(double[]) - Method in class com.imsl.chart.Bar: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.BarItem: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.BarSet: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.BoxPlot: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Contour: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Data: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Dendrogram: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.ErrorBar: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.Heatmap: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.HighLowClose: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.qc.ControlLimit: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.qc.CuSum: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart.qc.ShewhartControlChart: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart3d.Data: Update the data range, range = {xmin,xmax,ymin,ymax}.
dataRange(double[]) - Method in class com.imsl.chart3d.Surface: Update the data range, range = {xmin,xmax,ymin,ymax}.
DAY - Static variable in class com.imsl.chart.HighLowClose: Milliseconds per day
DayCountBasis - Class in com.imsl.finance: The Day Count Basis.
DayCountBasis(BasisPart, BasisPart) - Constructor for class com.imsl.finance.DayCountBasis: Creates a new DayCountBasis.
daysBetween(GregorianCalendar, GregorianCalendar) - Method in interface com.imsl.finance.BasisPart: Returns the number of days from date1 to date2.
daysInPeriod(GregorianCalendar, int) - Method in interface com.imsl.finance.BasisPart: Returns the number of days in a coupon period.
db(double, double, int, int, int) - Static method in class com.imsl.finance.Finance: Returns the depreciation of an asset using the fixed-declining balance method.
ddb(double, double, int, int, double) - Static method in class com.imsl.finance.Finance: Returns the depreciation of an asset using the double-declining balance method.
decode(double) - Method in class com.imsl.datamining.neural.ScaleFilter: Unscales a value.
decode(double[]) - Method in class com.imsl.datamining.neural.ScaleFilter: Unscales an array of values.
decode(int, double[][]) - Method in class com.imsl.datamining.neural.ScaleFilter: Unscales a single column of a two dimensional array of values.
decode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter: Decodes a binary encoded array into its nominal category.
decode(int[][]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter: Decodes a matrix representing the binary encoded columns of the nominal variable.
decode(double) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Decodes an encoded ordinal variable.
decode(double[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Decodes an array of encoded ordinal values.
defineConstant(String, Physical) - Static method in class com.imsl.math.Physical: Defines a new constant.
definePrefix(String, double) - Static method in class com.imsl.math.Physical: Defines a new prefix.
defineUnit(String, Physical) - Static method in class com.imsl.math.Physical: Defines a new unit.
deleteRow() - Method in class com.imsl.io.AbstractFlatFile: Deletes the current row from this ResultSet object and from the underlying database.
Dendrogram - Class in com.imsl.chart: A Dendrogram chart for cluster analysis.
Dendrogram(AxisXY, ClusterHierarchical) - Constructor for class com.imsl.chart.Dendrogram: Constructs a vertical dendrogram chart using supplied ClusterHierarchical object.
Dendrogram(AxisXY, double[], int[], int[]) - Constructor for class com.imsl.chart.Dendrogram: Constructs a vertical dendrogram chart using supplied data.
Dendrogram(AxisXY, ClusterHierarchical, int) - Constructor for class com.imsl.chart.Dendrogram: Constructs a dendrogram chart using supplied ClusterHierarchical object.
Dendrogram(AxisXY, double[], int[], int[], int) - Constructor for class com.imsl.chart.Dendrogram: Constructs a dendrogram chart using supplied data.
DENDROGRAM_TYPE_HORIZONTAL - Static variable in class com.imsl.chart.ChartNode: Flag to indicate a horizontal dendrogram.
DENDROGRAM_TYPE_VERTICAL - Static variable in class com.imsl.chart.ChartNode: Flag to indicate a vertical dendrogram.
DenseLP - Class in com.imsl.math: Solves a linear programming problem using an active set strategy.
DenseLP(MPSReader) - Constructor for class com.imsl.math.DenseLP: Constructor using an MPSReader object.
DenseLP(double[][], double[], double[]) - Constructor for class com.imsl.math.DenseLP: Constructor variables of type double.
DenseLP.BoundsInconsistentException - Exception in com.imsl.math: The bounds given are inconsistent.
DenseLP.BoundsInconsistentException(String) - Constructor for exception com.imsl.math.DenseLP.BoundsInconsistentException
DenseLP.BoundsInconsistentException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.BoundsInconsistentException
DenseLP.NoAcceptablePivotException - Exception in com.imsl.math: No acceptable pivot could be found.
DenseLP.NoAcceptablePivotException(String) - Constructor for exception com.imsl.math.DenseLP.NoAcceptablePivotException
DenseLP.NoAcceptablePivotException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.NoAcceptablePivotException
DenseLP.ProblemUnboundedException - Exception in com.imsl.math: The problem is unbounded.
DenseLP.ProblemUnboundedException(String) - Constructor for exception com.imsl.math.DenseLP.ProblemUnboundedException
DenseLP.ProblemUnboundedException(String, Object[]) - Constructor for exception com.imsl.math.DenseLP.ProblemUnboundedException
derivative(double, double) - Method in interface com.imsl.datamining.neural.Activation: Returns the value of the derivative of the activation function.
derivative(double) - Method in class com.imsl.math.BSpline: Returns the value of the first derivative of the B-spline at a point.
derivative(double, int) - Method in class com.imsl.math.BSpline: Returns the value of the derivative of the B-spline at a point.
derivative(double[], int) - Method in class com.imsl.math.BSpline: Returns the value of the derivative of the B-spline at each point of an array.
derivative(double) - Method in class com.imsl.math.Spline: Returns the value of the first derivative of the spline at a point.
derivative(double, int) - Method in class com.imsl.math.Spline: Returns the value of the derivative of the spline at a point.
derivative(double[], int) - Method in class com.imsl.math.Spline: Returns the value of the derivative of the spline at each point of an array.
derivative(double, double, int, int) - Method in class com.imsl.math.Spline2D: Returns the value of the partial derivative of the tensor-product spline at the point (x, y).
derivative(double[], double[], int, int) - Method in class com.imsl.math.Spline2D: Returns the values of the partial derivative of the tensor-product spline of an array of points.
derivative(double[], int, double[], double[], double[]) - Method in interface com.imsl.stat.NonlinearRegression.Derivative: Computes the weight, frequency, and partial derivatives of the residual given the parameter vector theta for a single observation.
descending(int[]) - Static method in class com.imsl.stat.Sort: Function to sort an integer array into descending order.
descending(int[], int[]) - Static method in class com.imsl.stat.Sort: Sort an integer array into descending order and returns the permutation vector.
descending(double[]) - Static method in class com.imsl.stat.Sort: Sort an array into descending order.
descending(double[], int[]) - Static method in class com.imsl.stat.Sort: Sort an array into descending order and returns the permutation vector.
descending(double[][], int) - Static method in class com.imsl.stat.Sort: Function to sort a matrix into descending order by the first nkeys.
descending(double[][], int[]) - Static method in class com.imsl.stat.Sort: Function to sort a matrix into descending order by specified keys.
descending(double[][], int, int[]) - Static method in class com.imsl.stat.Sort: Function to sort an array into descending order by the first nkeys and returns the permutation vector.
descending(double[][], int[], int[]) - Static method in class com.imsl.stat.Sort: Function to sort a matrix into descending order by specified keys and return the permutation vector.
determinant() - Method in class com.imsl.math.ComplexLU: Return the determinant of the matrix used to construct this instance.
determinant() - Method in class com.imsl.math.LU: Return the determinant of the matrix used to construct this instance.
diagonal(int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a diagonal pattern.
diamond(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a diamond pattern (a checkerboard rotated 45 degrees).
diamondHatch(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a crosshatch on a 45 degree angle.
Difference - Class in com.imsl.stat: Differences a seasonal or nonseasonal time series.
Difference() - Constructor for class com.imsl.stat.Difference: Constructor for Difference.
dim - Variable in class com.imsl.math.Physical
DIRECT_AT_RESTART_AND_TERMINATION - Static variable in class com.imsl.math.GenMinRes: Indicates residual updating is to be done by direct evaluation upon restarting and at termination.
DIRECT_AT_RESTART_ONLY - Static variable in class com.imsl.math.GenMinRes: Indicates residual updating is to be done by direct evaluation upon restarting only.
DirectionalLight - Class in com.imsl.chart3d: A directional light.
DirectionalLight(Chart3D) - Constructor for class com.imsl.chart3d.DirectionalLight: Creates a directional light pointing in the negative z direction.
DirectionalLight(Chart3D, double, double, double) - Constructor for class com.imsl.chart3d.DirectionalLight: Creates a directional light pointing with a specified direction.
disc(GregorianCalendar, GregorianCalendar, double, double, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the implied interest rate of a discount bond.
discreteUniform(int, int) - Static method in class com.imsl.stat.Cdf: Evaluates the discrete uniform cumulative probability distribution function.
discreteUniformProb(int, int) - Static method in class com.imsl.stat.Cdf: Evaluates the discrete uniform probability density function.
DiscriminantAnalysis - Class in com.imsl.stat: Performs a linear or a quadratic discriminant function analysis among several known groups and the use of either reclassification, split sample, or the leaving-out-one methods in order to evaluate the rule.
DiscriminantAnalysis(int, int) - Constructor for class com.imsl.stat.DiscriminantAnalysis: Constructor for DiscriminantAnalysis.
DiscriminantAnalysis.CovarianceSingularException - Exception in com.imsl.stat: The variance-Covariance matrix is singular.
DiscriminantAnalysis.CovarianceSingularException(String) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException
DiscriminantAnalysis.CovarianceSingularException(String, Object[]) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.CovarianceSingularException
DiscriminantAnalysis.EmptyGroupException - Exception in com.imsl.stat: There are no observations in a group.
DiscriminantAnalysis.EmptyGroupException(String) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.EmptyGroupException
DiscriminantAnalysis.EmptyGroupException(String, Object[]) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.EmptyGroupException
DiscriminantAnalysis.SumOfWeightsNegException - Exception in com.imsl.stat: The sum of the weights have become negative.
DiscriminantAnalysis.SumOfWeightsNegException(String) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException
DiscriminantAnalysis.SumOfWeightsNegException(String, Object[]) - Constructor for exception com.imsl.stat.DiscriminantAnalysis.SumOfWeightsNegException
Dissimilarities - Class in com.imsl.stat: Computes a matrix of dissimilarities (or similarities) between the columns (or rows) of a matrix.
Dissimilarities(double[][], int, int, int) - Constructor for class com.imsl.stat.Dissimilarities: Constructor for Dissimilarities.
Dissimilarities(double[][], int, int, int, int[]) - Constructor for class com.imsl.stat.Dissimilarities: Constructor for Dissimilarities.
Dissimilarities.NoPositiveVarianceException - Exception in com.imsl.stat: No variable has positive variance.
Dissimilarities.NoPositiveVarianceException() - Constructor for exception com.imsl.stat.Dissimilarities.NoPositiveVarianceException: Constructs a NoPositiveVarianceException.
Dissimilarities.ScaleFactorZeroException - Exception in com.imsl.stat: The computations cannot continue because a scale factor is zero.
Dissimilarities.ScaleFactorZeroException(int) - Constructor for exception com.imsl.stat.Dissimilarities.ScaleFactorZeroException: Constructs a ScaleFactorZeroException.
Dissimilarities.ZeroNormException - Exception in com.imsl.stat: The computations cannot continue because the Euclidean norm of the column is equal to zero.
Dissimilarities.ZeroNormException(int) - Constructor for exception com.imsl.stat.Dissimilarities.ZeroNormException: Constructs a ZeroNormException.
divide(Complex, Complex) - Static method in class com.imsl.math.Complex: Returns the result of a Complex object divided by a Complex object, x/y.
divide(Complex, double) - Static method in class com.imsl.math.Complex: Returns the result of a Complex object divided by a double, x/y.
divide(double, Complex) - Static method in class com.imsl.math.Complex: Returns the result of a double divided by a Complex object, x/y.
divide(Physical, Physical) - Static method in class com.imsl.math.Physical: Divide two Physical objects.
divide(Physical, double) - Static method in class com.imsl.math.Physical: Divide a Physical object by a double.
divide(double, Physical) - Static method in class com.imsl.math.Physical: Divide a double by a Physical object.
doGet(HttpServletRequest, HttpServletResponse) - Method in class com.imsl.chart.ChartServlet: Returns the chart as a PNG image.
doGetBytes(int) - Method in class com.imsl.io.AbstractFlatFile: Implements the actual getBytes().
doGetBytes(int) - Method in class com.imsl.io.FlatFile: Gets the value of the designated column in the current row as a byte array.
dollarde(double, int) - Static method in class com.imsl.finance.Finance: Converts a fractional price to a decimal price.
dollarfr(double, int) - Static method in class com.imsl.finance.Finance: Converts a decimal price to a fractional price.
doNext() - Method in class com.imsl.io.AbstractFlatFile: Implements the operations on the file required by the method next().
doNext() - Method in class com.imsl.io.FlatFile: Moves the cursor down one row from its current position.
dot(int, int, Color, Color) - Static method in class com.imsl.chart.FillPaint: Returns a pattern that is an array of circles.
doubleValue() - Method in class com.imsl.math.Complex: Returns the value of the real part as a double.
doubleValue() - Method in class com.imsl.math.Physical: Returns the value of this dimensionless object.
downdate(double[]) - Method in class com.imsl.math.Cholesky: Downdates the factorization by subtracting a rank-1 matrix.
downdateX(double[]) - Method in class com.imsl.stat.NormTwoSample: Removes the observations in x from the first sample.
downdateY(double[]) - Method in class com.imsl.stat.NormTwoSample: Removes the observations in y from the second sample.
Draw - Class in com.imsl.chart: Chart tree renderer.
Draw(Graphics, Dimension) - Constructor for class com.imsl.chart.Draw: Contructs a Draw object.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.Draw: Draws the outline of a circular or elliptical arc covering the specified rectangle.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawMap: Draws the outline of a circular or elliptical arc covering the specified rectangle.
drawArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawPick: Draw an arc.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.Draw: Draw an error bar.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.DrawMap: Draw an error bar.
drawErrorBar(int, int, int, int, int) - Method in class com.imsl.chart.DrawPick: Draw ErrorBar
drawImage(Image, int, int) - Method in class com.imsl.chart.Draw: Draw an image.
drawImage(Image, int, int) - Method in class com.imsl.chart.DrawMap: Draw Image
drawImage(Image, int, int) - Method in class com.imsl.chart.DrawPick: Draw Image
drawLine(int, int, int, int) - Method in class com.imsl.chart.Draw: Draw a line from (x0,y0) to (x1,y1).
drawLine(int, int, int, int) - Method in class com.imsl.chart.DrawMap: Draw a line from (x0,y0) to (x1,y1).
drawLine(int, int, int, int) - Method in class com.imsl.chart.DrawPick: Draw a line from (x0,y0) to (x1,y1).
DrawMap - Class in com.imsl.chart: Creates an HTML client-side imagemap from a chart tree.
DrawMap(Graphics, Dimension) - Constructor for class com.imsl.chart.DrawMap: Contructs a DrawMap object.
drawMarker(int, int) - Method in class com.imsl.chart.Draw: Draw a marker.
drawMarker(int, int) - Method in class com.imsl.chart.DrawMap: Draw a marker.
drawMarker(int, int) - Method in class com.imsl.chart.DrawPick: Draw a marker.
DrawPick - Class in com.imsl.chart: The DrawPick class.
DrawPick(MouseEvent, Graphics, Dimension) - Constructor for class com.imsl.chart.DrawPick: Contructs a DrawPick object.
drawRotatedText(Text, int, int, float) - Method in class com.imsl.chart.Draw: Draws a text object, at the specified angle, with its lower left point being at (x,y).
drawText(Text, int, int) - Method in class com.imsl.chart.Draw: Draws a text object.
drawText(Text, int, int, boolean) - Method in class com.imsl.chart.Draw: Draws a text object.
drawText(Graphics, Text) - Method in class com.imsl.chart.Draw: Draws the text.
drawText(Text, int, int, boolean) - Method in class com.imsl.chart.DrawMap
drawText(Text, int, int) - Method in class com.imsl.chart.DrawPick
Dummy - Class in com.imsl
Dummy() - Constructor for class com.imsl.Dummy
duration(GregorianCalendar, GregorianCalendar, double, double, int, DayCountBasis) - Static method in class com.imsl.finance.Bond: Returns the Macauley's duration of a security where the security has periodic interest payments.

E

E - Static variable in class com.imsl.math.JMath
effect(double, int) - Static method in class com.imsl.finance.Finance: Returns the effective annual interest rate.
Eigen - Class in com.imsl.math: Collection of Eigen System functions.
Eigen(double[][]) - Constructor for class com.imsl.math.Eigen: Constructs the eigenvalues and the eigenvectors of a real square matrix.
Eigen(double[][], boolean) - Constructor for class com.imsl.math.Eigen: Constructs the eigenvalues and (optionally) the eigenvectors of a real square matrix.
Eigen.DidNotConvergeException - Exception in com.imsl.math: The iteration did not converge
Eigen.DidNotConvergeException(String) - Constructor for exception com.imsl.math.Eigen.DidNotConvergeException
Eigen.DidNotConvergeException(String, Object[]) - Constructor for exception com.imsl.math.Eigen.DidNotConvergeException
EmpiricalQuantiles - Class in com.imsl.stat: Computes empirical quantiles.
EmpiricalQuantiles(double[], double[]) - Constructor for class com.imsl.stat.EmpiricalQuantiles: Constructor for EmpiricalQuantiles.
EmpiricalQuantiles.ScaleFactorZeroException - Exception in com.imsl.stat: The computations cannot continue because a scale factor is zero.
EmpiricalQuantiles.ScaleFactorZeroException(int) - Constructor for exception com.imsl.stat.EmpiricalQuantiles.ScaleFactorZeroException: Constructs a ScaleFactorZeroException.
encode(double) - Method in class com.imsl.datamining.neural.ScaleFilter: Scales a value.
encode(double[]) - Method in class com.imsl.datamining.neural.ScaleFilter: Scales an array of values.
encode(int, double[][]) - Method in class com.imsl.datamining.neural.ScaleFilter: Scales a single column of a two dimensional array of values.
encode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter: Encodes class data prior to its use in neural network training.
encode(int) - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter: Apply forward encoding to a value.
encode(int[]) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Encodes an array of ordinal categories into an array of transformed percentages.
encode(int) - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Encodes an ordinal category.
END_COLUMN_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a column label is to be returned.
END_COLUMN_LABELS - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a column label row is to be returned.
END_ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatted string for ending an entry is to be returned.
END_MATRIX - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a matrix is to be returned.
END_ROW - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a row is to be returned.
END_ROW_LABEL - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatting string for ending a row label is to be returned.
endErrorBar() - Method in class com.imsl.chart.Draw: Stop drawing an error bar.
endErrorBar() - Method in class com.imsl.chart.DrawMap
endErrorBar() - Method in class com.imsl.chart.DrawPick: End ErrorBar
endFill() - Method in class com.imsl.chart.Draw: Stop drawing a filled region.
endFill() - Method in class com.imsl.chart.DrawMap
endFill() - Method in class com.imsl.chart.DrawPick: End fill
endImage() - Method in class com.imsl.chart.Draw: Stop drawing an image.
endImage() - Method in class com.imsl.chart.DrawMap
endImage() - Method in class com.imsl.chart.DrawPick: End Image
endLine() - Method in class com.imsl.chart.Draw: Finish drawing lines.
endLine() - Method in class com.imsl.chart.DrawMap
endLine() - Method in class com.imsl.chart.DrawPick: Finish drawing lines.
endMarker() - Method in class com.imsl.chart.Draw: Finish drawing markers.
endMarker() - Method in class com.imsl.chart.DrawMap
endMarker() - Method in class com.imsl.chart.DrawPick: Finish drawing markers.
endText() - Method in class com.imsl.chart.Draw: Stop drawing text.
endText() - Method in class com.imsl.chart.DrawMap
endText() - Method in class com.imsl.chart.DrawPick: End Text
ENTRY - Static variable in class com.imsl.math.PrintMatrixFormat: This flag as the type argument to format, indicates that the formatted string for a given entry is to be returned.
EpochTrainer - Class in com.imsl.datamining.neural: Two-stage training using randomly selected training patterns in stage I.
EpochTrainer(Trainer) - Constructor for class com.imsl.datamining.neural.EpochTrainer: Creates a single stage EpochTrainer.
EpochTrainer(Trainer, Trainer) - Constructor for class com.imsl.datamining.neural.EpochTrainer: Creates an two-stage EpochTrainer.
EPSILON_LARGE - Static variable in class com.imsl.math.Sfun: The largest relative spacing for doubles.
EPSILON_LARGE - Static variable in class com.imsl.math.Spline: The largest relative spacing for double.
EPSILON_SMALL - Static variable in class com.imsl.math.QuadraticProgramming: The smallest relative spacing for doubles.
EPSILON_SMALL - Static variable in class com.imsl.math.Sfun: The smallest relative spacing for doubles.
EPSILON_SMALL - Static variable in class com.imsl.math.ZeroPolynomial: The smallest relative spacing for doubles.
EpsilonAlgorithm - Class in com.imsl.math: The class is used to determine the limit of a sequence of approximations, by means of the Epsilon algorithm of P.
EpsilonAlgorithm() - Constructor for class com.imsl.math.EpsilonAlgorithm: Initializes an EpsilonAlgorithm with a maximum table size of 50.
EpsilonAlgorithm(int) - Constructor for class com.imsl.math.EpsilonAlgorithm: Initializes an EpsilonAlgorithm.
equals(Complex) - Method in class com.imsl.math.Complex: Compares with another Complex.
equals(Object) - Method in class com.imsl.math.Complex: Compares this object against the specified object.
erf(double) - Static method in class com.imsl.math.Sfun: Returns the error function of a double.
erfc(double) - Static method in class com.imsl.math.Sfun: Returns the complementary error function of a double.
erfcInverse(double) - Static method in class com.imsl.math.Sfun: Returns the inverse of the complementary error function.
erfInverse(double) - Static method in class com.imsl.math.Sfun: Returns the inverse of the error function.
error(String, Object[]) - Method in class com.imsl.chart.xml.ChartXML: Handles error messages.
error(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML: Receive notification of a recoverable error.
error(double[], double[]) - Method in interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error: Returns the contribution to the error from a single training output target.
ERROR_BAR - Static variable in class com.imsl.chart.Draw
ErrorBar - Class in com.imsl.chart: Data points with error bars.
ErrorBar(AxisXY, double[], double[], double[], double[]) - Constructor for class com.imsl.chart.ErrorBar: Creates a set of error bars centered at (x[k],y[k]) and with extents low[k],high[k].
errorGradient(double[], double[]) - Method in interface com.imsl.datamining.neural.QuasiNewtonTrainer.Error: Returns the derivative of the error function with respect to the forecast output.
eval(HyperRectangleQuadrature.Function) - Method in class com.imsl.math.HyperRectangleQuadrature: Returns the value of the integral over the unit cube.
eval(HyperRectangleQuadrature.Function, double[], double[]) - Method in class com.imsl.math.HyperRectangleQuadrature: Returns the value of the integral over a cube.
eval(Quadrature.Function, double, double) - Method in class com.imsl.math.Quadrature: Returns the value of the integral from a to b.
eval(double, double) - Method in class com.imsl.stat.InverseCdf: Evaluates the inverse CDF function.
EWMA - Class in com.imsl.chart.qc: EWMA is an exponentially weighted moving average control chart.
EWMA(AxisXY, double[], double) - Constructor for class com.imsl.chart.qc.EWMA: Creates an exponentially weighted moving average chart.
EWMA(AxisXY, double[], double, double, double) - Constructor for class com.imsl.chart.qc.EWMA: Creates an exponentially weighted moving average chart using the given values for the expected mean and standard deviation.
examineStep(int, double, double[]) - Method in class com.imsl.math.OdeRungeKutta: Called before and after each internal step.
excludeFirst(boolean) - Method in class com.imsl.stat.Difference: If set to true, the observations lost due to differencing will be excluded.
exp(Complex) - Static method in class com.imsl.math.Complex: Returns the exponential of a Complex z, exp(z).
exp(double) - Static method in class com.imsl.math.JMath: Returns the exponential of a double.
expectedNormalOrderStatistic(int, int) - Static method in class com.imsl.stat.Ranks: Returns the expected value of a normal order statistic.
expm1(double) - Static method in class com.imsl.math.Hyperbolic: Returns exp(x)-1, the exponential of x minus 1.
exponential(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the exponential cumulative probability distribution function.
exponentialProb(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the exponential probability density function
extrapolate(double) - Method in class com.imsl.math.EpsilonAlgorithm: Extrapolates the convergence limit of a sequence.
extremeValue(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the extreme value cumulative probability distribution function.
extremeValueProb(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the extreme value probability density function.

F

f(double) - Method in interface com.imsl.chart.ChartFunction: Function to be charted.
f(double) - Method in class com.imsl.chart.ChartSpline: Function to be charted.
f(double, double) - Method in interface com.imsl.chart3d.Surface.ZFunction: Define the surface function.
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockGradObjective
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.BlockObjective
f(double[]) - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer.Objective
f(double[]) - Method in interface com.imsl.math.HyperRectangleQuadrature.Function: Returns the value of the function at the given point.
f(double[]) - Method in interface com.imsl.math.MinConGenLin.Function: Public interface for the function to be minimized.
f(double[], int, boolean[]) - Method in interface com.imsl.math.MinConNLP.Function: Compute the value of the function at the given point.
f(double) - Method in interface com.imsl.math.MinUncon.Function: Public interface for the smooth function of a single variable to be minimized.
f(double[]) - Method in interface com.imsl.math.MinUnconMultiVar.Function: Public interface for the multivariate function to be minimized.
f(double[], double[]) - Method in interface com.imsl.math.NonlinLeastSquares.Function: Public interface for the nonlinear least-squares function.
f(double, double[], double[]) - Method in interface com.imsl.math.OdeRungeKutta.Function: Returns the value of the function at the given point.
f(double) - Method in interface com.imsl.math.Quadrature.Function: Returns the value of the function at the given point.
f(double) - Method in interface com.imsl.math.RadialBasis.Function: A radial basis function.
f(double) - Method in class com.imsl.math.RadialBasis.Gaussian
f(double) - Method in class com.imsl.math.RadialBasis.HardyMultiquadric
f(double) - Method in interface com.imsl.math.ZeroFunction.Function: Returns the value of the function at the given point.
f(double[], double[]) - Method in interface com.imsl.math.ZeroSystem.Function: Returns the value of the function at the given point.
F(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the F cumulative probability distribution function.
f(double[], int, double[], double[], double[]) - Method in interface com.imsl.stat.NonlinearRegression.Function: Computes the weight, frequency, and residual given the parameter vector theta for a single observation.
FACE_XA - Static variable in class com.imsl.chart3d.AxisBox: Show the x = a face of the box.
FACE_XB - Static variable in class com.imsl.chart3d.AxisBox: Show the x = b face of the box.
FACE_YA - Static variable in class com.imsl.chart3d.AxisBox: Show the y = a face of the box.
FACE_YB - Static variable in class com.imsl.chart3d.AxisBox: Show the y = b face of the box.
FACE_ZA - Static variable in class com.imsl.chart3d.AxisBox: Show the z = a face of the box.
FACE_ZB - Static variable in class com.imsl.chart3d.AxisBox: Show the z = b face of the box.
fact(int) - Static method in class com.imsl.math.Sfun: Returns the factorial of an integer.
factor - Variable in class com.imsl.math.ComplexLU: This is an n by n Complex matrix containing the LU factorization of the matrix A.
factor - Variable in class com.imsl.math.LU: This is an n by n matrix containing the LU factorization of the matrix A.
FactorAnalysis - Class in com.imsl.stat: Performs Principal Component Analysis or Factor Analysis on a covariance or correlation matrix.
FactorAnalysis(double[][], int, int) - Constructor for class com.imsl.stat.FactorAnalysis: Constructor for FactorAnalysis.
FactorAnalysis.BadVarianceException - Exception in com.imsl.stat: Bad variance error.
FactorAnalysis.BadVarianceException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.BadVarianceException
FactorAnalysis.BadVarianceException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.BadVarianceException
FactorAnalysis.EigenvalueException - Exception in com.imsl.stat: Eigenvalue error.
FactorAnalysis.EigenvalueException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.EigenvalueException
FactorAnalysis.EigenvalueException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.EigenvalueException
FactorAnalysis.NoDegreesOfFreedomException - Exception in com.imsl.stat: No degrees of freedom error.
FactorAnalysis.NoDegreesOfFreedomException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NoDegreesOfFreedomException
FactorAnalysis.NoDegreesOfFreedomException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NoDegreesOfFreedomException
FactorAnalysis.NonPositiveEigenvalueException - Exception in com.imsl.stat: Non positive eigenvalue error.
FactorAnalysis.NonPositiveEigenvalueException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException
FactorAnalysis.NonPositiveEigenvalueException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NonPositiveEigenvalueException
FactorAnalysis.NotPositiveDefiniteException - Exception in com.imsl.stat: Covariance matrix not positive definite.
FactorAnalysis.NotPositiveDefiniteException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NotPositiveDefiniteException
FactorAnalysis.NotPositiveDefiniteException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NotPositiveDefiniteException
FactorAnalysis.NotPositiveSemiDefiniteException - Exception in com.imsl.stat: Covariance matrix not positive semi-definite.
FactorAnalysis.NotPositiveSemiDefiniteException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException
FactorAnalysis.NotPositiveSemiDefiniteException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NotPositiveSemiDefiniteException
FactorAnalysis.NotSemiDefiniteException - Exception in com.imsl.stat: Hessian matrix not semi-definite.
FactorAnalysis.NotSemiDefiniteException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.NotSemiDefiniteException
FactorAnalysis.NotSemiDefiniteException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.NotSemiDefiniteException
FactorAnalysis.RankException - Exception in com.imsl.stat: Rank of covariance matrix error.
FactorAnalysis.RankException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.RankException
FactorAnalysis.RankException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.RankException
FactorAnalysis.SingularException - Exception in com.imsl.stat: Covariance matrix singular error.
FactorAnalysis.SingularException(String) - Constructor for exception com.imsl.stat.FactorAnalysis.SingularException
FactorAnalysis.SingularException(String, Object[]) - Constructor for exception com.imsl.stat.FactorAnalysis.SingularException
factorNumerically() - Method in class com.imsl.math.ComplexSparseCholesky: Computes the numeric factorization of a sparse Hermitian positive definite matrix.
factorNumerically() - Method in class com.imsl.math.SparseCholesky: Computes the numeric factorization of a sparse real symmetric positive definite matrix.
factorSymbolically() - Method in class com.imsl.math.ComplexSparseCholesky: Computes the symbolic factorization of a sparse Hermitian positive definite matrix.
factorSymbolically() - Method in class com.imsl.math.SparseCholesky: Computes the symbolic factorization of a sparse real symmetric positive definite matrix.
fatalError(SAXParseException) - Method in class com.imsl.chart.xml.ChartXML: Receive notification of a non-recoverable error.
FaureSequence - Class in com.imsl.stat: Generates the low-discrepancy Faure sequence.
FaureSequence(int) - Constructor for class com.imsl.stat.FaureSequence: Creates a Faure sequence with the default base.
FaureSequence(int, int, int) - Constructor for class com.imsl.stat.FaureSequence: Creates a Faure sequence.
FeedForwardNetwork - Class in com.imsl.datamining.neural: A representation of a feed forward neural network.
FeedForwardNetwork() - Constructor for class com.imsl.datamining.neural.FeedForwardNetwork: Creates a new instance of FeedForwardNetwork.
FFT - Class in com.imsl.math: FFT functions.
FFT(int) - Constructor for class com.imsl.math.FFT: Constructs an FFT object.
FILL - Static variable in class com.imsl.chart.Draw
FILL_FACTOR - Static variable in class com.imsl.math.ComplexSuperLU: A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
FILL_FACTOR - Static variable in class com.imsl.math.SuperLU: A performance tuning parameter which can be adjusted via method setPerformanceTuningParameters.
FILL_TYPE_GRADIENT - Static variable in class com.imsl.chart.ChartNode: Value for attribute "FillType" indicating that the region is to be drawn in a color gradient as specified by the attribute Gradient.
FILL_TYPE_NONE - Static variable in class com.imsl.chart.ChartNode: Value for attribute "FillType" and "FillOutlineType" indicating that the region is not to be drawn.
FILL_TYPE_PAINT - Static variable in class com.imsl.chart.ChartNode: Value for attribute "FillType" indicating that the region is to be drawn using the texture specified by the attribute FillPaint.
FILL_TYPE_SOLID - Static variable in class com.imsl.chart.ChartNode: Value for attribute "FillType" and "FillOutlineType" indicating that the region is to be drawn using the solid color specified by the attribute FillColor or FillOutlineColor.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.Draw: Fills a circular or elliptical arc covering the specified rectangle.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawMap: Fills a circular or elliptical arc covering the specified rectangle.
fillArc(int, int, int, int, int, int) - Method in class com.imsl.chart.DrawPick: Fills a circular or elliptical arc covering the specified rectangle.
fillColor - Variable in class com.imsl.chart.Draw
fillOutlineColor - Variable in class com.imsl.chart.Draw
fillOutlineType - Variable in class com.imsl.chart.Draw
fillPaint - Variable in class com.imsl.chart.Draw
FillPaint - Class in com.imsl.chart: A collection of methods to create Paint objects for fill areas.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.Draw: Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.Draw: Fill a polygon defined by a Polygon object.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.DrawMap: Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.DrawMap: Fill a polygon defined by a Polygon object.
fillPolygon(int[], int[], int) - Method in class com.imsl.chart.DrawPick: Fill a polygon.
fillPolygon(Polygon) - Method in class com.imsl.chart.DrawPick: Fill a polygon defined by a Polygon object.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.Draw: Fill a rectangle.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.DrawMap: Fill a rectangle.
fillRectangle(int, int, int, int) - Method in class com.imsl.chart.DrawPick: Fill a rectangle.
fillType - Variable in class com.imsl.chart.Draw
filter() - Method in class com.imsl.stat.KalmanFilter: Performs Kalman filtering and evaluates the likelihood function for the state-space model.
finalize() - Method in class com.imsl.chart.Chart
finalize() - Method in class com.imsl.chart3d.Chart3D
Finance - Class in com.imsl.finance: Collection of finance functions.
findColumn(String) - Method in class com.imsl.io.AbstractFlatFile: Maps the given ResultSet column name to its ResultSet column index.
findColumnName(int) - Method in class com.imsl.io.AbstractFlatFile: Maps the given columnIndex into its column name.
findLink(Node, Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the Link between two Nodes.
findLinks(Node) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns all of the Links to a given Node.
finite(double) - Static method in class com.imsl.math.IEEE: Finite number test on an argument of type double.
fire() - Method in class com.imsl.chart.DrawPick: Fires the pickListeners for all of the picked nodes.
firePickListeners(MouseEvent) - Method in class com.imsl.chart.ChartNode: Fires the pick listeners defined at this node and at all of its ancestors, if the event "hits" the node.
first() - Method in class com.imsl.io.AbstractFlatFile: Moves the cursor to the first row in this ResultSet object.
FIRST_DERIVATIVE - Static variable in class com.imsl.math.CsInterpolate
FIRST_GRAM_SCHMIDT - Static variable in class com.imsl.math.GenMinRes: Indicates the first Gram-Schmidt implementation method is to be used.
FIRST_HOUSEHOLDER - Static variable in class com.imsl.math.GenMinRes: Indicates the first Householder implementation method is to be used.
FlatFile - Class in com.imsl.io: Reads a text file as a ResultSet.
FlatFile(BufferedReader, Tokenizer) - Constructor for class com.imsl.io.FlatFile: Creates a FlatFile from a BufferedReader.
FlatFile(BufferedReader) - Constructor for class com.imsl.io.FlatFile: Creates a FlatFile with the CSV tokenizer.
FlatFile(String) - Constructor for class com.imsl.io.FlatFile: Creates a FlatFile from a CSV file.
FlatFile(String, Tokenizer) - Constructor for class com.imsl.io.FlatFile: Creates a FlatFile from a file with the default tokenizer.
FlatFile.Parser - Interface in com.imsl.io: Defines a method that parses a String into an Object.
floatValue() - Method in class com.imsl.math.Complex: Returns the value of the real part as a float.
floatValue() - Method in class com.imsl.math.Physical: Returns the value of this dimensionless object.
floor(double) - Static method in class com.imsl.math.JMath: Returns the value of a double rounded toward negative infinity to an integral value.
forecast(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Computes a forecast using the Network.
forecast(double[]) - Method in class com.imsl.datamining.neural.Network: Returns a forecast for each of the Network's outputs computed from the trained Network.
forecast(int) - Method in class com.imsl.stat.ARAutoUnivariate: Returns forecasts and associated confidence interval offsets.
forecast(int) - Method in class com.imsl.stat.ARMA: Computes forecasts and their associated probability limits for an ARMA model.
forecast(int) - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns forecasts for lead times at origins z.length-backwardOrigin-1+j where .
format(LogRecord) - Method in class com.imsl.math.GenMinRes.Formatter
format(LogRecord) - Method in class com.imsl.math.MinConNLP.Formatter
format(int, Object, int, int, ParsePosition) - Method in class com.imsl.math.PrintMatrixFormat: Returns a formatted string.
format(LogRecord) - Method in class com.imsl.stat.ARAutoUnivariate.Formatter
formatLabel(double, double) - Method in class com.imsl.chart.Data
formatMessage(String, String, Object[]) - Static method in class com.imsl.Messages: A message is formatted using a MessageFormat string retrieved from the named resource bundle using the given key.
formatMessage(String, String) - Static method in class com.imsl.Messages: A message is formatted, without arguments, using a MessageFormat string retrieved from the named resource bundle using the given key.
forward(Complex[]) - Method in class com.imsl.math.ComplexFFT: Compute the Fourier coefficients of a complex periodic sequence.
forward(double[]) - Method in class com.imsl.math.FFT: Compute the Fourier coefficients of a real periodic sequence.
FORWARD_REGRESSION - Static variable in class com.imsl.stat.StepwiseRegression: Indicates forward regression.
FProb(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the F probability density function.
frobeniusNorm(Complex[][]) - Static method in class com.imsl.math.ComplexMatrix: Return the Frobenius norm of a Complex matrix.
frobeniusNorm() - Method in class com.imsl.math.ComplexSparseMatrix: Returns the Frobenius norm of the matrix.
frobeniusNorm(double[][]) - Static method in class com.imsl.math.Matrix: Return the Frobenius norm of a matrix.
frobeniusNorm() - Method in class com.imsl.math.SparseMatrix: Returns the Frobenius norm of the matrix.
FULL - Static variable in class com.imsl.math.PrintMatrix: This flag as the argument to setMatrixType, indicates that the full matrix is to be printed.
fv(double, int, double, double, int) - Static method in class com.imsl.finance.Finance: Returns the future value of an investment.
fvschedule(double, double[]) - Static method in class com.imsl.finance.Finance: Returns the future value of an initial principal taking into consideration a schedule of compound interest rates.

G

g(double) - Method in interface com.imsl.datamining.neural.Activation: Returns the value of the activation function.
g(double) - Method in interface com.imsl.math.MinUncon.Derivative: Public interface for the smooth function of a single variable to be minimized.
g(double) - Method in interface com.imsl.math.RadialBasis.Function: The derivative of the radial basis function.
g(double) - Method in class com.imsl.math.RadialBasis.Gaussian
g(double) - Method in class com.imsl.math.RadialBasis.HardyMultiquadric
gamma(double) - Static method in class com.imsl.math.Sfun: Returns the Gamma function of a double.
gamma(double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the gamma cumulative probability distribution function.
gammaProb(double, double, double) - Static method in class com.imsl.stat.Cdf: Evaluates the gamma probability density function.
GARCH - Class in com.imsl.stat: Computes estimates of the parameters of a GARCH(p,q) model.
GARCH(int, int, double[], double[]) - Constructor for class com.imsl.stat.GARCH: Constructor for GARCH.
GARCH.ConstrInconsistentException - Exception in com.imsl.stat: The equality constraints are inconsistent.
GARCH.ConstrInconsistentException(String) - Constructor for exception com.imsl.stat.GARCH.ConstrInconsistentException
GARCH.ConstrInconsistentException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.ConstrInconsistentException
GARCH.EqConstrInconsistentException - Exception in com.imsl.stat: The equality constraints and the bounds on the variables are found to be inconsistent.
GARCH.EqConstrInconsistentException(String) - Constructor for exception com.imsl.stat.GARCH.EqConstrInconsistentException
GARCH.EqConstrInconsistentException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.EqConstrInconsistentException
GARCH.NoVectorXException - Exception in com.imsl.stat: No vector X satisfies all of the constraints.
GARCH.NoVectorXException(String) - Constructor for exception com.imsl.stat.GARCH.NoVectorXException
GARCH.NoVectorXException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.NoVectorXException
GARCH.TooManyIterationsException - Exception in com.imsl.stat: Number of function evaluations exceeded 1000.
GARCH.TooManyIterationsException(String) - Constructor for exception com.imsl.stat.GARCH.TooManyIterationsException
GARCH.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.TooManyIterationsException
GARCH.VarsDeterminedException - Exception in com.imsl.stat: The variables are determined by the equality constraints.
GARCH.VarsDeterminedException(String) - Constructor for exception com.imsl.stat.GARCH.VarsDeterminedException
GARCH.VarsDeterminedException(String, Object[]) - Constructor for exception com.imsl.stat.GARCH.VarsDeterminedException
GENERALIZED_LEAST_SQUARES - Static variable in class com.imsl.stat.FactorAnalysis: Indicates generalized least squares method.
GenMinRes - Class in com.imsl.math: Linear system solver using the restarted Generalized Minimum Residual (GMRES) method.
GenMinRes(int, GenMinRes.Function) - Constructor for class com.imsl.math.GenMinRes: GMRES linear system solver constructor.
GenMinRes.Formatter - Class in com.imsl.math: Simple formatter for GenMinRes logging
GenMinRes.Formatter() - Constructor for class com.imsl.math.GenMinRes.Formatter
GenMinRes.Function - Interface in com.imsl.math: Public interface for the user supplied function to GenMinRes.
GenMinRes.Norm - Interface in com.imsl.math: Public interface for the user supplied function to the GenMinRes object used for the norm when the Gram-Schmidt implementation is used.
GenMinRes.Preconditioner - Interface in com.imsl.math: Public interface for the user supplied function to GenMinRes used for preconditioning.
GenMinRes.TooManyIterationsException - Exception in com.imsl.math: Maximum number of iterations exceeded.
GenMinRes.TooManyIterationsException(String) - Constructor for exception com.imsl.math.GenMinRes.TooManyIterationsException
GenMinRes.TooManyIterationsException(String, Object[]) - Constructor for exception com.imsl.math.GenMinRes.TooManyIterationsException
GenMinRes.VectorProducts - Interface in com.imsl.math: Public interface for the user supplied function to the GenMinRes object used for the inner product when the Gram-Schmidt implementation is used.
geometric(int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the discrete geometric cumulative probability distribution function.
geometricProb(int, double) - Static method in class com.imsl.stat.Cdf: Evaluates the discrete geometric probability density function.
get(String) - Method in class com.imsl.chart.xml.ChartXML: Returns a generated object given the id attribute in the XML tag that created the object.
get(int, int) - Method in class com.imsl.math.ComplexSparseMatrix: Returns the value of an element in the matrix.
get(int, int) - Method in class com.imsl.math.SparseMatrix: Returns the value of an element in the matrix.
getAbsoluteH() - Method in class com.imsl.chart.qc.CuSumStatus: Returns the value for H used for setting limits.
getAbstractParent() - Method in class com.imsl.chart.AbstractChartNode: Returns the parent of this node.
getActivation() - Method in class com.imsl.datamining.neural.Perceptron: Returns the activation function.
getAdjustedRSquared() - Method in class com.imsl.stat.ANOVA: Returns the adjusted R-squared (in percent).
getAIC() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the final estimate for Akaike's Information Criterion (AIC) at the optimum.
getAIC() - Method in class com.imsl.stat.ARSeasonalFit: Returns the final estimate for Akaike's Information Criterion (AIC) at the optimum.
getAkaike() - Method in class com.imsl.stat.GARCH: Returns the value of Akaike Information Criterion evaluated at the estimated parameter array.
getAlignment() - Method in class com.imsl.chart.Text: Gets the alignment for this Text object.
getALT() - Method in class com.imsl.chart.ChartNode: Returns the value of the "ALT" attribute.
getALT() - Method in class com.imsl.chart.DrawMap: Returns the current ALT string.
getANOVA() - Method in class com.imsl.math.RadialBasis: Returns the ANOVA statistics from the linear regression.
getANOVA() - Method in class com.imsl.stat.LinearRegression: Get an analysis of variance table and related statistics.
getANOVA() - Method in class com.imsl.stat.StepwiseRegression: Get an analysis of variance table and related statistics.
getANOVA() - Method in class com.imsl.stat.UserBasisRegression: Get an analysis of variance table and related statistics.
getANOVATable() - Method in class com.imsl.stat.ANOVAFactorial: Returns the analysis of variance table.
getAR() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the final auto regressive parameter estimates at the optimum AIC using the estimation method specified in setEstimationMethod.
getAR() - Method in class com.imsl.stat.ARMA: Returns the final autoregressive parameter estimates.
getAR() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the final autoregressive parameter estimates.
getAR() - Method in class com.imsl.stat.ARSeasonalFit: Returns the final autoregressive parameter estimates at the optimum in the transformed series .
getAR() - Method in class com.imsl.stat.GARCH: Returns the estimated values of autoregressive (AR) parameters.
getAROrder() - Method in class com.imsl.stat.ARSeasonalFit: Returns optimum number of lags, p, for the optimum autoregressive AR(p) model.
getArray(int) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as an Array object in the Java programming language.
getArray(String) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as an Array object in the Java programming language.
getArray() - Method in class com.imsl.stat.ANOVA: Returns the ANOVA values as an array.
getAsciiStream(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a stream of ASCII characters.
getAsciiStream(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a stream of ASCII characters.
getAttribute(String) - Method in class com.imsl.chart.AbstractChartNode: Gets an attribute.
getAutoCorrelations() - Method in class com.imsl.stat.AutoCorrelation: Returns the autocorrelations of the time series x.
getAutoCorrelationX() - Method in class com.imsl.stat.CrossCorrelation: Returns the autocorrelations of the time series x.
getAutoCorrelationY() - Method in class com.imsl.stat.CrossCorrelation: Returns the autocorrelations of the time series y.
getAutoCovariance() - Method in class com.imsl.stat.ARMA: Returns the autocovariances of the time series z.
getAutoCovariances() - Method in class com.imsl.stat.AutoCorrelation: Returns the variance and autocovariances of the time series x.
getAutoCovarianceX() - Method in class com.imsl.stat.CrossCorrelation: Returns the autocovariances of the time series x.
getAutoCovarianceY() - Method in class com.imsl.stat.CrossCorrelation: Returns the autocovariances of the time series y.
getAutoscaleInput() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "AutoscaleInput" attribute.
getAutoscaleMinimumTimeInterval() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "AutoscaleMinimumTimeInterval" attribute.
getAutoscaleOutput() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "AutoscaleOutput" attribute.
getAxis() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Axis" attribute.
getAxisBox() - Method in class com.imsl.chart3d.AxisXYZ: Return the axis box node.
getAxisLabel() - Method in class com.imsl.chart.Axis1D: Returns the label node associated with this axis.
getAxisLabel() - Method in class com.imsl.chart3d.Axis3D: Returns the label node associated with this axis.
getAxisLine() - Method in class com.imsl.chart.Axis1D: Returns the axis line node associated with this axis.
getAxisLine() - Method in class com.imsl.chart3d.Axis3D: Returns the axis line node associated with this axis.
getAxisR() - Method in class com.imsl.chart.Polar: Return the radius axis node.
getAxisRLabel() - Method in class com.imsl.chart.AxisR: Returns the AxisRLabel node.
getAxisRLine() - Method in class com.imsl.chart.AxisR: Returns the AxisRLine node.
getAxisRMajorTick() - Method in class com.imsl.chart.AxisR: Returns the major tick node associated with this axis.
getAxisTheta() - Method in class com.imsl.chart.Polar: Return the angular axis node.
getAxisTitle() - Method in class com.imsl.chart.Axis1D: Returns the title node associated with this axis.
getAxisTitle() - Method in class com.imsl.chart3d.Axis3D: Returns the title node associated with this axis.
getAxisTitlePosition() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "AxisTitlePosition" attribute.
getAxisUnit() - Method in class com.imsl.chart.Axis1D: Returns the unit node associated with this axis.
getAxisX() - Method in class com.imsl.chart.AxisXY: Return the x-axis node.
getAxisX() - Method in class com.imsl.chart3d.AxisXYZ: Return the x-axis node.
getAxisY() - Method in class com.imsl.chart.AxisXY: Return the y-axis node.
getAxisY() - Method in class com.imsl.chart3d.AxisXYZ: Return the y-axis node.
getAxisZ() - Method in class com.imsl.chart3d.AxisXYZ: Return the z-axis node.
getBackground() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Background" attribute.
getBackground() - Method in class com.imsl.chart3d.Chart3D: Returns the value of the "Background" attribute.
getBackwardOrigin() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the maximum backward origin.
getBackwardOrigin() - Method in class com.imsl.stat.ARMA: Returns the user-specified backward origin
getBackwardOrigin() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the current value for forecasting backward origin.
getBalancedTable() - Method in class com.imsl.stat.TableMultiWay: Returns an object containing the balanced table.
getBarData() - Method in class com.imsl.chart.Bar: Returns the "BarData" attribute.
getBarGap() - Method in class com.imsl.chart.ChartNode: Returns the value of the "BarGap" attribute.
getBarItem() - Method in class com.imsl.chart.BarSet: Returns an array of BarItems.
getBarItem(int) - Method in class com.imsl.chart.BarSet: Returns the BarItem given the index.
getBarMinus() - Method in class com.imsl.chart.qc.CuSumStatus: Returns the value of the attribute "BarMinus" containing the $C^{-}$ bars.
getBarPlus() - Method in class com.imsl.chart.qc.CuSumStatus: Returns the value of the attribute "BarPlus" containing the $C^{+}$ bars.
getBarSet() - Method in class com.imsl.chart.Bar: Returns the BarSet object.
getBarSet(int, int) - Method in class com.imsl.chart.Bar: Returns the BarSet object.
getBarSet(int) - Method in class com.imsl.chart.Bar: Returns the BarSet object.
getBarType() - Method in class com.imsl.chart.ChartNode: Returns the value of the "BarType" attribute.
getBarWidth() - Method in class com.imsl.chart.ChartNode: Returns the value of the "BarWidth" attribute.
getBase() - Method in class com.imsl.stat.FaureSequence: Returns the base.
getBias() - Method in class com.imsl.datamining.neural.Perceptron: Returns the bias for this Perceptron.
getBigDecimal(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.math.BigDecimal with full precision.
getBigDecimal(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.math.BigDecimal with full precision.
getBinaryStream(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a binary stream of uninterpreted bytes.
getBinaryStream(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a stream of uninterpreted bytes.
getBlob(int) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a Blob object in the Java programming language.
getBlob(String) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a Blob object in the Java programming language.
getBlomScores(double[]) - Method in class com.imsl.stat.Ranks: Gets the Blom version of normal scores for each observation.
getBodies() - Method in class com.imsl.chart.BoxPlot: Returns a node containing the body elements in the Box plot.
getBoolean(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a boolean in the Java programming language.
getBoolean(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a boolean in the Java programming language.
getBooleanAttribute(String, boolean) - Method in class com.imsl.chart.AbstractChartNode: Convenience routine to get a Boolean-valued attribute.
getBoundingSphere() - Method in class com.imsl.chart3d.ChartNode3D: Gets the spherical bounding region object BoundingSphere.
getBounds() - Method in class com.imsl.datamining.neural.ScaleFilter: Retrieves bounds used during bounded scaling.
getBoxPlotType() - Method in class com.imsl.chart.BoxPlot: Returns the value of the "BoxPlotType" attribute.
getBreakpoints() - Method in class com.imsl.math.Spline: Returns a copy of the breakpoints.
getByte(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a byte in the Java programming language.
getByte(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a byte in the Java programming language.
getBytes(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a byte array in the Java programming language.
getBytes(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a byte array in the Java programming language.
getCanvas() - Method in class com.imsl.chart3d.Chart3D
getCanvas() - Method in class com.imsl.chart3d.JFrameChart3D: Returns the Canvas3DChart into which the chart is drawn.
getCaseAnalysis() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the case analysis.
getCaseStatistics(double[], double) - Method in class com.imsl.stat.LinearRegression: Returns the case statistics for an observation.
getCaseStatistics(double[], double, double) - Method in class com.imsl.stat.LinearRegression: Returns the case statistics for an observation and a weight.
getCaseStatistics(double[], double, int) - Method in class com.imsl.stat.LinearRegression: Returns the case statistics for an observation and future response count for the desired prediction interval.
getCaseStatistics(double[], double, double, int) - Method in class com.imsl.stat.LinearRegression: Returns the case statistics for an observation, weight, and future response count for the desired prediction interval.
getCDF() - Static method in class com.imsl.stat.KaplanMeierECDF: Retrieve CDF values up to, but not including the time values in x
getCellCounts() - Method in class com.imsl.stat.ChiSquaredTest: Returns the cell counts.
getCenter() - Method in class com.imsl.chart.qc.ShewhartControlChart: Returns the value of the attribute "Center".
getCenter() - Method in class com.imsl.datamining.neural.ScaleFilter: Retrieves the measure of center to be used during z-score scaling.
getCenter() - Method in class com.imsl.stat.ARSeasonalFit: Returns the current setting for centering the input time series.
getCenterLine() - Method in class com.imsl.chart.qc.ShewhartControlChart: Returns the center line.
getCharacterStream(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.
getCharacterStream(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.io.Reader object.
getChart() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Chart" attribute.
getChart(HttpServletRequest) - Method in class com.imsl.chart.ChartServlet: Returns the chart found in the session saved with the key "chart"+id, where id is the value of the "id" parameter in the request.
getChart() - Method in class com.imsl.chart.JFrameChart: Return the Chart object.
getChart() - Method in class com.imsl.chart.JPanelChart: Return the Chart object.
getChart() - Method in class com.imsl.chart.xml.ChartXML: Returns the root node of the chart tree.
getChart3D() - Method in class com.imsl.chart3d.Canvas3DChart: Returns the Chart3D associated with this canvas.
getChart3D() - Method in class com.imsl.chart3d.JFrameChart3D: Return the Chart object.
getChartServletName() - Method in class com.imsl.chart.JspBean: Returns the URL of the servlet used to render the chart.
getChartTitle() - Method in class com.imsl.chart.ChartNode: Returns the value of the "ChartTitle" attribute.
getChildList() - Method in class com.imsl.chart.AbstractChartNode: Returns the children of this node.
getChildren() - Method in class com.imsl.chart.ChartNode: Returns an array of the children of this node.
getChildren() - Method in class com.imsl.chart3d.ChartNode3D: Returns an array of the children of this node.
getChiSquared() - Method in class com.imsl.stat.ChiSquaredTest: Returns the chi-squared statistic.
getChiSquared() - Method in class com.imsl.stat.ContingencyTable: Returns the Pearson chi-squared test statistic.
getChiSquared() - Method in class com.imsl.stat.NormalityTest: Returns the chi-square statistic for the chi-squared goodness-of-fit test.
getChiSquaredTest() - Method in class com.imsl.stat.NormOneSample: Returns the test statistic associated with the chi-squared test for variances.
getChiSquaredTest() - Method in class com.imsl.stat.NormTwoSample: Returns the test statistic associated with the chi-squared test for common, or pooled, variances.
getChiSquaredTestDF() - Method in class com.imsl.stat.NormOneSample: Returns the degrees of freedom associated with the chi-squared test for variances.
getChiSquaredTestDF() - Method in class com.imsl.stat.NormTwoSample: Returns the degrees of freedom associated with the chi-squared test for the common, or pooled, variances.
getChiSquaredTestP() - Method in class com.imsl.stat.NormOneSample: Returns the probability of a larger chi-squared associated with the chi-squared test for variances.
getChiSquaredTestP() - Method in class com.imsl.stat.NormTwoSample: Returns the probability of a larger chi-squared associated with the chi-squared test for common, or pooled, variances.
getClassificationVariableCounts() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the number of values taken by each classification variable.
getClassificationVariableValues() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the distinct values of the classification variables in ascending order.
getClassMembership() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the group number to which the observation was classified.
getClassTable() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the classification table.
getClipBounds() - Method in class com.imsl.chart.Draw: Get the clipping rectangle.
getClipData() - Method in class com.imsl.chart.ChartNode: Returns the value of the "ClipData" attribute.
getClob(int) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a Clob object in the Java programming language.
getClob(String) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a Clob object in the Java programming language.
getClose() - Method in class com.imsl.chart.HighLowClose: Gets the value of the attribute "Close".
getClusterCounts() - Method in class com.imsl.stat.ClusterKMeans: Returns the number of observations in each cluster.
getClusterLeftSons() - Method in class com.imsl.stat.ClusterHierarchical: Returns the left sons of each merged cluster.
getClusterLevel() - Method in class com.imsl.stat.ClusterHierarchical: Returns the level at which the clusters are joined.
getClusterMembership(int) - Method in class com.imsl.stat.ClusterHierarchical: Returns the cluster membership of each observation.
getClusterMembership() - Method in class com.imsl.stat.ClusterKMeans: Returns the cluster membership for each observation.
getClusterRightSons() - Method in class com.imsl.stat.ClusterHierarchical: Returns the right sons of each merged cluster.
getClusterSSQ() - Method in class com.imsl.stat.ClusterKMeans: Returns the within sum of squares for each cluster.
getCMinus() - Method in class com.imsl.chart.qc.CuSumStatus: Returns the $C^{-}$ values.
getCoefficient(int) - Method in class com.imsl.stat.LinearRegression.CoefficientTTests: Returns the estimate for a coefficient.
getCoefficient(int) - Method in class com.imsl.stat.NonlinearRegression: Returns the estimate for a coefficient.
getCoefficient(int) - Method in class com.imsl.stat.StepwiseRegression.CoefficientTTests: Returns the estimate for a coefficient of the independent variable.
getCoefficientOfVariation() - Method in class com.imsl.stat.ANOVA: Returns the coefficient of variation (in percent).
getCoefficients() - Method in class com.imsl.io.MPSReader.Row: Returns the coeffients of this row as a dense array.
getCoefficients() - Method in class com.imsl.math.Spline2D: Returns the coefficients for the tensor-product spline.
getCoefficients() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the linear discriminant function coefficients.
getCoefficients() - Method in class com.imsl.stat.LinearRegression: Returns the regression coefficients.
getCoefficients() - Method in class com.imsl.stat.NonlinearRegression: Returns the regression coefficients.
getCoefficients() - Method in class com.imsl.stat.UserBasisRegression: Returns the regression coefficients.
getCoefficientStatistics(int) - Method in class com.imsl.stat.SelectionRegression.Statistics: Returns the coefficients statistics for each of the best regressions found for each subset considered.
getCoefficientTTests() - Method in class com.imsl.stat.LinearRegression: Returns statistics relating to the regression coefficients.
getCoefficientTTests() - Method in class com.imsl.stat.StepwiseRegression: Returns the student-t test statistics for the regression coefficients.
getCoefficientVIF() - Method in class com.imsl.stat.StepwiseRegression: Returns the variance inflation factors for the final model in this invocation.
getColorAttribute(String) - Method in class com.imsl.chart.AbstractChartNode: Convenience routine to get a Color-valued attribute.
getColorFunction() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "ColorFunction" attribute.
getColormap() - Method in class com.imsl.chart.Heatmap: Returns the value of the "Colormap" attribute.
getColumn() - Method in class com.imsl.io.MPSReader.Element: Returns the column index.
getColumnClass(int) - Method in class com.imsl.io.AbstractFlatFile: Returns the class of the items in the specified column.
getColumnCount() - Method in class com.imsl.io.AbstractFlatFile: Returns the number of columns in this ResultSet object.
getColumnCount() - Method in class com.imsl.io.FlatFile: Returns the number of columns in this ResultSet object.
getColumnPermutationMethod() - Method in class com.imsl.math.ComplexSuperLU: Returns the method that will be used to permute the columns of the input matrix.
getColumnPermutationMethod() - Method in class com.imsl.math.SuperLU: Returns the method that will be used to permute the columns of the input matrix.
getCompleteTimes() - Method in class com.imsl.stat.ARMAEstimateMissing: Returns an int array of all time points, including values for times with missing values in z.
getCompleteTimeSeries() - Method in class com.imsl.stat.ARMAEstimateMissing: Returns a double precision vector of length tpoints[tpoints.length-1]-tpoints[0]+1 containing the observed values in the time series z plus estimates for missing values in gaps identified in tpoints.
getComponent() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Component" attribute.
getConcatenatedViewport() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Viewport" attribute concatenated with the "Viewport" attributes set in its ancestor nodes.
getConcatenatedViewport() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "Viewport" attribute concatenated with the "Viewport" attributes set in its ancestor nodes.
getConcurrency() - Method in class com.imsl.io.AbstractFlatFile: Returns the concurrency mode of this ResultSet object.
getConditionNumber() - Method in class com.imsl.math.ComplexSuperLU: Returns the estimate of the reciprocal condition number of the matrix A.
getConditionNumber() - Method in class com.imsl.math.SuperLU: Returns the estimate of the reciprocal condition number of the matrix A.
getConfidence() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the confidence level for calculating confidence limit deviations returned from getDeviations.
getConfidence() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the confidence level used for calculating deviations in getDeviations.
getConfidenceInterval() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the Confidence Interval on the mean for an observation.
getConstant() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the estimate for the constant parameter in the ARMA series.
getConstant() - Method in class com.imsl.stat.ARMA: Returns the constant parameter estimate.
getConstant() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the estimate for the constant parameter in the ARMA series.
getConstraintResiduals() - Method in class com.imsl.math.MinConNLP: Returns the constraint residuals.
getContingencyCoef() - Method in class com.imsl.stat.ContingencyTable: Returns contingency coefficient.
getContourLegend() - Method in class com.imsl.chart.Contour: Returns the contour chart legend.
getContourLevel() - Method in class com.imsl.chart.Contour: Returns all of the contour levels.
getContourLevel(int) - Method in class com.imsl.chart.Contour: Returns a ContourLevel.
getContributions() - Method in class com.imsl.stat.ContingencyTable: Returns the contributions to chi-squared for each cell in the table.
getControlData() - Method in class com.imsl.chart.qc.ShewhartControlChart: Returns the Data object for the control data.
getControlLimit() - Method in class com.imsl.chart.qc.ControlLimit: Returns the value of the attribute "ControlLimit".
getConvergenceTolerance() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the tolerance level used to determine convergence of the nonlinearleast-squares and maximum likelihood algorithms.
getConvergenceTolerance() - Method in class com.imsl.stat.ARMAEstimateMissing: Returns the current value of convergence tolerance used by the AR_1 and AR_P estimation methods.
getCooksDistance() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns Cook's Distance for an observation.
getCoordinates() - Method in class com.imsl.chart.Dendrogram: Convenience routine to get the "Coordinates" attribute.
getCorrelations() - Method in class com.imsl.stat.FactorAnalysis: Returns the correlations of the principal components.
getCount() - Method in class com.imsl.stat.FaureSequence
getCovariance() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the array of covariances.
getCovarianceMatrix() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the estimated asymptotic covariance matrix of the coefficients.
getCovariancesSwept() - Method in class com.imsl.stat.StepwiseRegression: Returns the results after cov has been swept for the columns corresponding to the variables in the model.
getCovB() - Method in class com.imsl.stat.KalmanFilter: Returns the mean squared error matrix for b divided by sigma squared.
getCovV() - Method in class com.imsl.stat.KalmanFilter: Returns the variance-covariance matrix of v divided by sigma squared.
getCPlus() - Method in class com.imsl.chart.qc.CuSumStatus: Returns the $C^{+}$ values.
getCramersV() - Method in class com.imsl.stat.ContingencyTable: Returns Cramer's V.
getCreateImageMap() - Method in class com.imsl.chart.JspBean: Returns true if a client-side imagemap is to be created.
getCriterionOption() - Method in class com.imsl.stat.SelectionRegression: Returns the criterion option used to calculate the regression estimates.
getCriterionValues(int) - Method in class com.imsl.stat.SelectionRegression.Statistics: Returns an array containing the values of the best criterion for the number of variables considered.
getCross() - Method in class com.imsl.chart.AxisXY: Returns the value of the "Cross" attribute.
getCrossCorrelation() - Method in class com.imsl.stat.CrossCorrelation: Returns the cross-correlations between the time series x and y.
getCrossCorrelation() - Method in class com.imsl.stat.MultiCrossCorrelation: Returns the cross-correlations between the channels of x and y.
getCrossCovariance() - Method in class com.imsl.stat.CrossCorrelation: Returns the cross-covariances between the time series x and y.
getCrossCovariance() - Method in class com.imsl.stat.MultiCrossCorrelation: Returns the cross-covariances between the channels of x and y.
getCumulativeAxis() - Method in class com.imsl.chart.qc.ParetoChart: Returns the "CumulativeAxis" attribute.
getCumulativeLine() - Method in class com.imsl.chart.qc.ParetoChart: Returns the "CumulativeLine" attribute.
getCursorName() - Method in class com.imsl.io.AbstractFlatFile: Gets the name of the SQL cursor used by this ResultSet object.
getCustomMarkerFactory() - Method in class com.imsl.chart3d.Data: Returns a custom marker factory.
getCustomTransform() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "CustomTransform" attribute.
getCutpoints() - Method in class com.imsl.stat.ChiSquaredTest: Returns the cutpoints.
getDataMarkers() - Method in class com.imsl.chart.qc.CuSumStatus: Returns the "DataMarkers" attribute containing the data markers.
getDataMarkersAxis() - Method in class com.imsl.chart.qc.CuSumStatus: Returns the "DataMarkersAxis" attribute containing the axis associated with the data markers.
getDataType() - Method in class com.imsl.chart.ChartNode: Returns the value of the "DataType" attribute.
getDataType() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "DataType" attribute.
getDate(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(int, Calendar) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDate(String, Calendar) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as a java.sql.Date object in the Java programming language.
getDaysInYear(GregorianCalendar, GregorianCalendar) - Method in interface com.imsl.finance.BasisPart: Returns the number of days in the year.
getDegreesOfFreedom() - Method in class com.imsl.stat.ChiSquaredTest: Returns the degrees of freedom in chi-squared.
getDegreesOfFreedom() - Method in class com.imsl.stat.ContingencyTable: Returns the degrees of freedom for the chi-squared tests associated with the table.
getDegreesOfFreedom() - Method in class com.imsl.stat.NormalityTest: Returns the degrees of freedom for the chi-squared goodness-of-fit test.
getDegreesOfFreedomForError() - Method in class com.imsl.stat.ANOVA: Returns the degrees of freedom for error.
getDegreesOfFreedomForModel() - Method in class com.imsl.stat.ANOVA: Returns the degrees of freedom for model.
getDensity() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Density" attribute.
getDesignVariableMeans() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the means of the design variables.
getDeviations() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the deviations used for calculating the forecast confidence limits.
getDeviations() - Method in class com.imsl.stat.ARMA: Returns the deviations used for calculating the forecast confidence limits.
getDeviations() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the deviations from each forecast used for calculating the forecast confidence limits.
getDeviceMarkerSize() - Method in class com.imsl.chart.Draw: Returns the marker size in device corrdinates.
getDFError() - Method in class com.imsl.stat.NonlinearRegression: Returns the degrees of freedom for error.
getDFFITS() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns DFFITS for an observation.
getDiagonalPivotThreshold() - Method in class com.imsl.math.ComplexSuperLU: Returns the threshold used for a diagonal entry to be an acceptable pivot.
getDiagonalPivotThreshold() - Method in class com.imsl.math.SuperLU: Returns the threshold used for a diagonal entry to be an acceptable pivot.
getDiffMean() - Method in class com.imsl.stat.NormTwoSample: Returns the difference in means, mean of x - mean of y.
getDimension() - Method in class com.imsl.stat.FaureSequence: Returns the dimension of the sequence.
getDimension() - Method in interface com.imsl.stat.RandomSequence: Returns the dimension of the sequence.
getDInitial() - Method in class com.imsl.stat.ARSeasonalFit: Returns the candidate values for d to evaluate.
getDirection() - Method in class com.imsl.chart3d.DirectionalLight: Returns the value of the "Direction" attribute.
getDistanceMatrix() - Method in class com.imsl.stat.Dissimilarities: Returns the distance matrix.
getDouble(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a double in the Java programming language.
getDouble(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a double in the Java programming language.
getDoubleAttribute(String, double) - Method in class com.imsl.chart.AbstractChartNode: Convenience routine to get a Double-valued attribute.
getDoubleBuffering() - Method in class com.imsl.chart.ChartNode: Returns the value of the "DoubleBuffering" attribute.
getDown() - Method in class com.imsl.chart.Candlestick: Returns the CandlestickItem for down days.
getDual() - Method in class com.imsl.math.QuadraticProgramming: Returns the dual (Lagrange multipliers).
getDualSolution() - Method in class com.imsl.math.DenseLP: Returns the dual solution.
getDummyMethod() - Method in class com.imsl.stat.RegressorsForGLM: Returns the dummy method.
getDunnSidak(int, int) - Method in class com.imsl.stat.ANOVA: Computes the confidence interval of i-th mean - j-th mean, using the Dunn-Sidak method.
getEffects() - Method in class com.imsl.stat.RegressorsForGLM: Returns the effects.
getEffectsColumns() - Method in class com.imsl.stat.RegressorsForGLM: Returns a mapping of effects to regressor columns.
getEnumValue(String) - Static method in class com.imsl.chart.xml.ChartXML: Returns the int corresponding to an enumeration.
getEpochSize() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the number of sample training patterns in each stage 1 epoch.
getEquilibrate() - Method in class com.imsl.math.ComplexSuperLU: Returns the equilibration flag.
getEquilibrate() - Method in class com.imsl.math.SuperLU: Returns the equilibration flag.
getEquilibrationMethod() - Method in class com.imsl.math.ComplexSuperLU: Returns information on the type of equilibration used before matrix factorization.
getEquilibrationMethod() - Method in class com.imsl.math.SuperLU: Returns information on the type of equilibration used before matrix factorization.
getError() - Method in class com.imsl.datamining.neural.BinaryClassification: Returns the error function for use by QuasiNewtonTrainer for training a binary classification network.
getError() - Method in class com.imsl.datamining.neural.MultiClassification: Returns the error function for use by QuasiNewtonTrainer for training a classification network.
getError() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the function used to compute the error to be minimized.
getErrorEstimate() - Method in class com.imsl.math.EpsilonAlgorithm: Returns the current error estimate.
getErrorEstimate() - Method in class com.imsl.math.HyperRectangleQuadrature: Returns an estimate of the relative error in the computed result.
getErrorEstimate() - Method in class com.imsl.math.Quadrature: Returns an estimate of the relative error in the computed result.
getErrorGradient() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the value of the gradient of the error function with respect to the weights.
getErrorGradient() - Method in interface com.imsl.datamining.neural.Trainer: Returns the value of the gradient of the error function with respect to the weights.
getErrorMeanSquare() - Method in class com.imsl.stat.ANOVA: Returns the error mean square.
getErrorNumber() - Method in exception com.imsl.LicenseManagerException: Returns the FlexLM error number for this exception.
getErrorStatus() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the training error status.
getErrorStatus() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Returns the error status from the trainer.
getErrorStatus() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the error status from the trainer.
getErrorStatus() - Method in interface com.imsl.datamining.neural.Trainer: Returns the error status.
getErrorStatus() - Method in class com.imsl.math.MinUnconMultiVar: Returns the non-fatal error status.
getErrorStatus() - Method in class com.imsl.math.NonlinLeastSquares: Get information about the performance of NonlinLeastSquares.
getErrorStatus() - Method in class com.imsl.math.Quadrature: Returns the non-fatal error status.
getErrorStatus() - Method in class com.imsl.stat.NonlinearRegression: Gets information about the performance of NonlinearRegression.
getErrorValue() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the value of the error function.
getErrorValue() - Method in class com.imsl.datamining.neural.LeastSquaresTrainer: Returns the final value of the error function.
getErrorValue() - Method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the final value of the error function.
getErrorValue() - Method in interface com.imsl.datamining.neural.Trainer: Returns the value of the error function minimized by the trainer.
getEstimationMethod() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the estimation method used for estimating the autoregressive coefficients.
getEstimationMethod() - Method in class com.imsl.stat.ARMAEstimateMissing: Returns the method used for estimating the final autoregressive coefficients for missing value estimation methods AR_1 and AR_P.
getExactMean() - Method in class com.imsl.stat.ContingencyTable: Returns exact mean.
getExactStdev() - Method in class com.imsl.stat.ContingencyTable: Returns exact standard deviation.
getExclude() - Method in class com.imsl.stat.ARSeasonalFit: Returns the current setting for excluding or replacing the inital values in the transformed series.
getExpectedCounts() - Method in class com.imsl.stat.ChiSquaredTest: Returns the expected counts.
getExpectedMean() - Method in class com.imsl.chart.qc.CuSum: Returns the expected mean of all of the data from all of the samples.
getExpectedMean() - Method in class com.imsl.chart.qc.CuSumStatus: Returns the expected (target) mean value.
getExpectedValues() - Method in class com.imsl.stat.ContingencyTable: Returns the expected values of each cell in the table.
getExplode() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Explode" attribute.
getExtendedLikelihoodObservations() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns a vector indicating which observations are included in the extended likelihood.
getF() - Method in class com.imsl.stat.ANOVA: Returns the F statistic.
getFactorLoadings() - Method in class com.imsl.stat.FactorAnalysis: Returns the unrotated factor loadings.
getFarMarkers() - Method in class com.imsl.chart.BoxPlot: Returns the FarMarkers node.
getFarMarkers() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the array of far markers.
getFeature() - Method in exception com.imsl.LicenseManagerException: Returns the name of the feature that could not be licensed.
getFetchDirection() - Method in class com.imsl.io.AbstractFlatFile: Returns the fetch direction for this ResultSet object.
getFetchSize() - Method in class com.imsl.io.AbstractFlatFile: Returns the fetch size for this ResultSet object.
getFillColor() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "FillColor" attribute.
getFillOutlineColor() - Method in class com.imsl.chart.ChartNode: Returns the value of the "FillOutlineColor" attribute.
getFillOutlineType() - Method in class com.imsl.chart.ChartNode: Returns the value of the "FillOutlineType" attribute.
getFillPaint() - Method in class com.imsl.chart.ChartNode: Returns the value of the "FillPaint" attribute.
getFillType() - Method in class com.imsl.chart.ChartNode: Returns the value of the "FillType" attribute.
getFinalActiveConstraints() - Method in class com.imsl.math.MinConGenLin: Returns the indices of the final active constraints.
getFinalActiveConstraintsNum() - Method in class com.imsl.math.MinConGenLin: Returns the final number of active constraints.
getFirstTick() - Method in class com.imsl.chart.Axis1D: Convenience routine to get the "FirstTick" attribute.
getFirstTick() - Method in class com.imsl.chart3d.Axis3D: Convenience routine to get the "FirstTick" attribute.
getFloat(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a float in the Java programming language.
getFloat(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a float in the Java programming language.
getFont() - Method in class com.imsl.chart.AbstractChartNode: Convenience routine which gets a Font object based on the "FontName", "FontStyle" and "FontSize" attributes.
getFontName() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "FontName" attribute.
getFontSize() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "FontSize" attribute.
getFontStyle() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "FontStyle" attribute.
getForecast(int) - Method in class com.imsl.stat.ARAutoUnivariate: Returns forecasts
getForecast(int) - Method in class com.imsl.stat.ARMA: Returns forecasts
getForecast(int) - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns forecasts
getForecastGradient(double[]) - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the derivatives of the outputs with respect to the weights.
getForecastGradient(double[]) - Method in class com.imsl.datamining.neural.Network: Returns the derivatives of the outputs with respect to the weights.
getFormatter() - Static method in class com.imsl.datamining.neural.EpochTrainer: Returns the logging Formatter object.
getFormatter() - Static method in class com.imsl.datamining.neural.LeastSquaresTrainer: Returns the logging Formatter object.
getFormatter() - Static method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the logging formatter object.
getForwardErrorBound() - Method in class com.imsl.math.ComplexSuperLU: Returns the estimated forward error bound for each solution vector.
getForwardErrorBound() - Method in class com.imsl.math.SuperLU: Returns the estimated forward error bound for the solution vector.
getFrequencyTable() - Method in class com.imsl.stat.TableOneWay: Returns the one-way frequency table.
getFrequencyTable(double, double) - Method in class com.imsl.stat.TableOneWay: Returns a one-way frequency table using known bounds.
getFrequencyTable() - Method in class com.imsl.stat.TableTwoWay: Returns the two-way frequency table.
getFrequencyTable(double, double, double, double) - Method in class com.imsl.stat.TableTwoWay: Compute a two-way frequency table using intervals of equal length and user supplied upper and lower bounds, xLowerBound, xUpperBound, yLowerBound, yUpperBound.
getFrequencyTableUsingClassmarks(double[]) - Method in class com.imsl.stat.TableOneWay: Returns the one-way frequency table using class marks.
getFrequencyTableUsingClassmarks(double[], double[]) - Method in class com.imsl.stat.TableTwoWay: Returns the two-way frequency table using either cutpoints or class marks.
getFrequencyTableUsingCutpoints(double[]) - Method in class com.imsl.stat.TableOneWay: Returns the one-way frequency table using cutpoints.
getFrequencyTableUsingCutpoints(double[], double[]) - Method in class com.imsl.stat.TableTwoWay: Returns the two-way frequency table using cutpoints.
getFrom() - Method in class com.imsl.datamining.neural.Link: Returns the origination Node for this Link.
getFTest() - Method in class com.imsl.stat.NormTwoSample: Returns the F test value of the F test for equality of variances.
getFTestDFdenominator() - Method in class com.imsl.stat.NormTwoSample: Returns the denominator degrees of freedom of the F test for equality of variances.
getFTestDFnumerator() - Method in class com.imsl.stat.NormTwoSample: Returns the numerator degrees of freedom of the F test for equality of variances.
getFTestP() - Method in class com.imsl.stat.NormTwoSample: Returns the probability of a larger F in absolute value for the F test for equality of variances, assuming equal variances.
getGradient() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Gradient" attribute.
getGradients() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the gradients for the final parameter estimates.
getGradientTolerance() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the gradient tolerance for the convergence algorithm.
getGrid() - Method in class com.imsl.chart.Axis1D: Returns the grid node associated with this axis.
getGridPolar() - Method in class com.imsl.chart.Polar: Returns the grid.
getGroupCounts() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the group counts.
getGroupInformation() - Method in class com.imsl.stat.ANOVA: Returns information concerning the groups.
getGroups() - Method in class com.imsl.stat.TableMultiWay: Returns the number of observations (rows) in each group.
getGSquared() - Method in class com.imsl.stat.ContingencyTable: Returns the likelihood ratio G² (chi-squared).
getGSquaredP() - Method in class com.imsl.stat.ContingencyTable: Returns the probability of a larger G² (chi-squared).
getGuess() - Method in class com.imsl.math.GenMinRes: Returns the initial guess of the solution.
getHeatmapLabels() - Method in class com.imsl.chart.Heatmap: Returns the value of the "HeatmapLabels" attribute.
getHeatmapLegend() - Method in class com.imsl.chart.Heatmap: Returns the heatmap legend.
getHessian() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the Hessian computed at the initial parameter estimates.
getHiddenLayers() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the HiddenLayers in this network.
getHigh() - Method in class com.imsl.chart.ErrorBar: Convenience routine to get the "High" attribute.
getHigh() - Method in class com.imsl.chart.HighLowClose: Convenience routine to get the "High" attribute.
getHistory() - Method in class com.imsl.stat.StepwiseRegression: Returns the stepwise regression history for the independent variables.
getHREF() - Method in class com.imsl.chart.ChartNode: Returns the value of the "HREF" attribute.
getHREF() - Method in class com.imsl.chart.DrawMap: Returns the current HREF string.
getId() - Method in class com.imsl.chart.JspBean: Returns the identifier number for the chart.
getImage() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Image" attribute.
getImageMap() - Method in class com.imsl.chart.JspBean: Returns an HTML for the client-side imagemap.
getImageTag() - Method in class com.imsl.chart.JspBean: Returns an HTML image tag.
getIncidenceMatrix() - Method in class com.imsl.stat.Covariances: Returns the incidence matrix.
getIndependentVariables(int) - Method in class com.imsl.stat.SelectionRegression.Statistics: Returns the identification numbers for the independent variables for the number of variables considered and in the same order as the criteria returned by SelectionRegression.Statistics.getCriterionValues(int).
getIndex() - Method in class com.imsl.datamining.neural.Layer: Returns the index of this Layer.
getInfo() - Method in class com.imsl.math.SVD: Returns convergence information about S, U, and V.
getInitialCMinus() - Method in class com.imsl.chart.qc.CuSumStatus: Returns the initial value of $C^{-}$ .
getInitialCPlus() - Method in class com.imsl.chart.qc.CuSumStatus: Returns the initial value of $C^{+}$ .
getInnovationVariance() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the final estimate for the innovation variance.
getInnovationVariance() - Method in class com.imsl.stat.ARMA: Returns the variance of the random shock.
getInnovationVariance() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the estimated innovation variance of this series.
getInputLayer() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the InputLayer.
getInputLayer() - Method in class com.imsl.datamining.neural.Network: Returns the InputLayer object.
getInt(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as an int in the Java programming language.
getInt(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as an int in the Java programming language.
getIntegerAttribute(String, int) - Method in class com.imsl.chart.AbstractChartNode: Convenience routine to get an Integer-valued attribute.
getIterationCount() - Method in class com.imsl.math.DenseLP: Returns the iteration count.
getIterations() - Method in class com.imsl.math.ConjugateGradient: Returns the number of iterations needed by the conjugate gradient algorithm.
getIterations() - Method in class com.imsl.math.GenMinRes: Returns the actual number of GMRES iterations used.
getIterations() - Method in class com.imsl.math.MinConNLP: Returns the actual number of iterations used.
getIterations() - Method in class com.imsl.math.MinUnconMultiVar: Returns the number of iterations used to compute a minimum.
getIterations(int) - Method in class com.imsl.math.ZeroFunction: Returns the number of iterations used to compute a root.
getIterativeRefinement() - Method in class com.imsl.math.ComplexSuperLU: Returns a value specifying whether iterative refinement is to be performed or not.
getIterativeRefinement() - Method in class com.imsl.math.SuperLU: Returns a value specifying whether iterative refinement is to be performed or not.
getJackknifeResidual() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the Jackknife Residual for an observation.
getJacobi() - Method in class com.imsl.math.ConjugateGradient: Returns the Jacobi preconditioning matrix.
getJacobian() - Method in class com.imsl.math.BoundedLeastSquares: Returns the Jacobian at the approximate solution.
getKeyboard() - Method in class com.imsl.chart3d.Chart3D: Returns the value of the "Keyboard" attribute.
getKnots() - Method in class com.imsl.math.BSpline: Returns a copy of the knot sequence.
getKurtosis() - Method in class com.imsl.stat.Summary: Returns the kurtosis.
getLabels() - Method in class com.imsl.chart.AxisLabel: Returns the "Labels" attribute.
getLabels() - Method in class com.imsl.chart.AxisRLabel: Returns the "Labels" attribute.
getLabels() - Method in class com.imsl.chart3d.AxisLabel: Returns the "Labels" attribute.
getLabelType() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "LabelType" attribute.
getLagrangeMultiplierEst() - Method in class com.imsl.math.MinConGenLin: Returns the Lagrange multiplier estimates of the final active constraints.
getLagrangeMultiplierEst() - Method in class com.imsl.math.MinConNLP: Returns the Lagrange multiplier estimates of the constraints.
getLambda() - Method in class com.imsl.chart.qc.EWMA: Returns the value of the attribute "Lambda".
getLargestDiagonalElement() - Method in class com.imsl.math.ComplexSparseCholesky: Returns the largest diagonal element of the Cholesky factor.
getLargestDiagonalElement() - Method in class com.imsl.math.SparseCholesky: Returns the largest diagonal element of the Cholesky factor.
getLastParameterUpdates() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the last parameter updates (excluding step halvings).
getLayer() - Method in class com.imsl.datamining.neural.Node: Returns the Layer in which this Node exists.
getLeftSons() - Method in class com.imsl.chart.Dendrogram: Convenience routine to get the "LeftSons" attribute.
getLegend() - Method in class com.imsl.chart.ChartNode: Returns the value of the "Legend" attribute.
getLevels() - Method in class com.imsl.chart.Dendrogram: Convenience routine to get the "Levels" attribute.
getLeverage() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the Leverage for an observation.
getLicensePath() - Method in exception com.imsl.LicenseManagerException: Returns the license file path for this exception.
getLightColor() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "LightColor" attribute.
getLightingEnabled() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "LightingEnabled" attribute.
getLikelihood() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the final estimate for $L=e^{-(mbox{AIC} - 2p)/2}$ , where p is the AR order, AIC is Akaike's Information Criterion, and L is the likelihood function evaluated for the optimum autoregressive model.
getLikelihood() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the final estimate for , where is equal to the likelihood function evaluated using the final parameter estimates.
getLineColor() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "LineColor" attribute.
getLineDashPattern() - Method in class com.imsl.chart.ChartNode: Returns the value of the "LineDashPattern" attribute.
getLineWidth() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "LineWidth" attribute.
getLinks() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Return all of the Links in this Network.
getLinks() - Method in class com.imsl.datamining.neural.Network: Returns an array containing the Link objects in the Network.
getListCells() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable: Returns for each row, a list of the levels of nKeys corresponding classification variables that describe a cell.
getLocale() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Locale" attribute.
getLocalizedMessage() - Method in exception com.imsl.LicenseManagerException: Returns the localized error message for this exception.
getLogDeterminant() - Method in class com.imsl.stat.KalmanFilter: Returns the natural log of the product of the nonzero eigenvalues of P where P * sigma² is the variance-covariance matrix of the observations.
getLogger() - Static method in class com.imsl.datamining.neural.EpochTrainer: Returns the Logger object.
getLogger() - Static method in class com.imsl.datamining.neural.LeastSquaresTrainer: Returns the Logger object.
getLogger() - Static method in class com.imsl.datamining.neural.QuasiNewtonTrainer: Returns the Logger object.
getLogger() - Method in class com.imsl.math.GenMinRes: Returns the logger object.
getLogger() - Method in class com.imsl.math.MinConNLP: Returns the logger object.
getLogger() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the logger object.
getLogLikelihood() - Method in class com.imsl.stat.GARCH: Returns the value of Log-likelihood function evaluated at the estimated parameter array.
getLong(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a long in the Java programming language.
getLong(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as a long in the Java programming language.
getLow() - Method in class com.imsl.chart.ErrorBar: Convenience routine to get the "Low" attribute.
getLow() - Method in class com.imsl.chart.HighLowClose: Convenience routine to get the "Low" attribute.
getLowerAdjacentValue() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the lower adjacent value.
getLowerBound(int) - Method in class com.imsl.io.MPSReader: Returns the lower bound for a variable.
getLowerCICommonVariance() - Method in class com.imsl.stat.NormTwoSample: Returns the lower confidence limits for the common, or pooled, variance.
getLowerCIDiff() - Method in class com.imsl.stat.NormTwoSample: Returns the lower confidence limit for the mean of the first population minus the mean of the second for equal or unequal variances depending on the value set by setUnequalVariances.
getLowerCIMean() - Method in class com.imsl.stat.NormOneSample: Returns the lower confidence limit for the mean.
getLowerCIRatioVariance() - Method in class com.imsl.stat.NormTwoSample: Returns the approximate lower confidence limit for the ratio of the variance of the first population to the second.
getLowerCIVariance() - Method in class com.imsl.stat.NormOneSample: Returns the lower confidence limits for the variance.
getLowerControlLimit() - Method in class com.imsl.chart.qc.ShewhartControlChart: Returns the lower control limit.
getLowerQuartile() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the lower quartile value.
getLowerRange(int) - Method in class com.imsl.io.MPSReader: Returns the lower range value for a constraint equation.
getMA() - Method in class com.imsl.stat.ARMA: Returns the final moving average parameter estimates.
getMA() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the final moving average parameter estimates.
getMA() - Method in class com.imsl.stat.GARCH: Returns the estimated values of moving average (MA) parameters.
getMahalanobis() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the Mahalanobis distances between the group means.
getMajorTick() - Method in class com.imsl.chart.Axis1D: Returns the major tick node associated with this axis.
getMajorTick() - Method in class com.imsl.chart3d.Axis3D: Returns the major tick node associated with this axis.
getMap() - Method in class com.imsl.chart.DrawMap: Returns the body of the HTML imagemap.
getMapName() - Method in class com.imsl.chart.JspBean: Returns the name of the client-size imagemap.
getMarkerColor() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "MarkerColor" attribute.
getMarkerDashPattern() - Method in class com.imsl.chart.ChartNode: Returns the value of the "MarkerPattern" attribute.
getMarkerPulsingCycle() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerPulsingCycle" attribute.
getMarkerPulsingCycleOffset() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerPulsingCycleOffset" attribute.
getMarkerPulsingMaximumScale() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerPulsingMaximumScale" attribute.
getMarkerPulsingMinimumScale() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerPulsingMinimumScale" attribute.
getMarkerRotatingAxis() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerRotatingAxis" attribute.
getMarkerRotatingCycle() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerRotatingCycle" attribute.
getMarkerRotatingCycleOffset() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerRotatingCycleOffset" attribute.
getMarkerSize() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "MarkerSize" attribute.
getMarkerThickness() - Method in class com.imsl.chart.ChartNode: Returns the value of the "MarkerThickness" attribute.
getMarkerType() - Method in class com.imsl.chart.ChartNode: Returns the value of the "MarkerType" attribute.
getMarkerType() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "MarkerType" attribute.
getMaterial() - Method in class com.imsl.chart3d.ChartNode3D: Returns the value of the "Material" attribute.
getMaxDifference() - Method in class com.imsl.stat.NormalityTest: Returns the maximum absolute difference between the empirical and the theoretical distributions for the Lilliefors test.
getMaximum() - Method in class com.imsl.stat.Summary: Returns the maximum.
getMaximum() - Method in class com.imsl.stat.TableOneWay: Returns maximum value of x.
getMaximumDifference() - Method in class com.imsl.stat.KolmogorovOneSample: Returns $D^{+}$ , the maximum difference between the theoretical and empirical CDF's.
getMaximumDifference() - Method in class com.imsl.stat.KolmogorovTwoSample: Returns $D^{+}$ , the maximum difference between the theoretical and empirical CDF's.
getMaximumTime() - Method in class com.imsl.math.MinConNLP: Returns the maximum time allowed for the solve step.
getMaximumValue() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the maximum value of the observations.
getMaximumValue() - Method in class com.imsl.chart.qc.ControlLimit: Returns the maximum value of this control limit line.
getMaximumX() - Method in class com.imsl.stat.TableTwoWay: Returns the maximum value of x.
getMaximumY() - Method in class com.imsl.stat.TableTwoWay: Returns the maximum value of y.
getMaxIterations() - Method in class com.imsl.math.ConjugateGradient: Returns the maximum number of iterations allowed.
getMaxIterations() - Method in class com.imsl.math.GenMinRes: Returns the maximum number of iterations allowed.
getMaxIterations() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the value currently being used as the maximum number of iterations allowed in the nonlinear equation solver used in both the method of moments and least-squares algorithms.
getMaxIterations() - Method in class com.imsl.stat.ARMAEstimateMissing: Returns the maximum number of estimation iterations used by missing value estimation methods AR_1 and AR_P.
getMaxIterations() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the maximum number of iterations.
getMaxKrylovDim() - Method in class com.imsl.math.GenMinRes: Returns the maximum Krylov subspace dimension, i.e., the maximum allowable number of GMRES iterations allowed before restarting.
getMaxlag() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the current value used to represent the maximum number of autoregressive lags to achieve the minimum AIC.
getMaxlag() - Method in class com.imsl.stat.ARMAEstimateMissing: Returns the current value of autoregressive lags used in the AR_P estimation method.
getMaxlag() - Method in class com.imsl.stat.ARSeasonalFit: Returns the maximum lag used to fit the AR(p) model.
getMean() - Method in class com.imsl.stat.ARAutoUnivariate: Returns the mean used to center the time series z.
getMean() - Method in class com.imsl.stat.ARMA: Returns an update of the mean of the time series z.
getMean() - Method in class com.imsl.stat.ARMAEstimateMissing: Returns the mean value used to center the series.
getMean() - Method in class com.imsl.stat.ARMAMaxLikelihood: Returns the mean used to center the time series.
getMean() - Method in class com.imsl.stat.AutoCorrelation: Returns the mean of the time series x.
getMean() - Method in class com.imsl.stat.NormOneSample: Returns the mean of the sample.
getMean() - Method in class com.imsl.stat.Summary: Returns the population mean.
getMeanOfY() - Method in class com.imsl.stat.ANOVA: Returns the mean of the response (dependent variable).
getMeans() - Method in class com.imsl.stat.ANOVAFactorial: Returns the subgroup means.
getMeans() - Method in class com.imsl.stat.Covariances: Returns the means of the variables in x.
getMeans() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the variable means.
getMeanSampleSize() - Method in class com.imsl.chart.qc.ShewhartControlChart: Returns the value of the attribute "MeanSampleSize".
getMeanX() - Method in class com.imsl.stat.CrossCorrelation: Returns the mean of the time series x.
getMeanX() - Method in class com.imsl.stat.MultiCrossCorrelation: Returns the mean of each channel of x.
getMeanX() - Method in class com.imsl.stat.NormTwoSample: Returns the mean of the first sample, x.
getMeanY() - Method in class com.imsl.stat.CrossCorrelation: Returns the mean of the time series y.
getMeanY() - Method in class com.imsl.stat.MultiCrossCorrelation: Returns the mean of each channel of y.
getMeanY() - Method in class com.imsl.stat.NormTwoSample: Returns the mean of the second sample, y.
getMedian() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the median value.
getMedianLowerConfidenceInterval() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the lower confidence interval for the median.
getMedianUpperConfidenceInterval() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the upper confidence interval for the median.
getMetaData() - Method in class com.imsl.io.AbstractFlatFile: Retrieves the number, types and properties of this ResultSet object's columns.
getMethod() - Method in class com.imsl.math.GenMinRes: Returns the implementation method to be used.
getMinimum() - Method in class com.imsl.stat.Summary: Returns the minimum.
getMinimum() - Method in class com.imsl.stat.TableOneWay: Returns the minimum value of x.
getMinimumDifference() - Method in class com.imsl.stat.KolmogorovOneSample: Returns $D^{-}$ , the minimum difference between the theoretical and empirical CDF's.
getMinimumDifference() - Method in class com.imsl.stat.KolmogorovTwoSample: Returns $D^{-}$ , the minimum difference between the theoretical and empirical CDF's.
getMinimumValue() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the minimum value of the observations.
getMinimumValue() - Method in class com.imsl.chart.qc.ControlLimit: Returns the minimum value of this control limit line.
getMinimumX() - Method in class com.imsl.stat.TableTwoWay: Returns the minimum value of x.
getMinimumY() - Method in class com.imsl.stat.TableTwoWay: Returns the minimum value of y.
getMinorTick() - Method in class com.imsl.chart.Axis1D: Returns the minor tick node associated with this axis.
getMissingTimes() - Method in class com.imsl.stat.ARMAEstimateMissing: Returns an int array of the times with missing values.
getMissingValueMethod() - Method in class com.imsl.stat.ARMAEstimateMissing: Returns the current missing value estimation method.
getModelErrorStdev() - Method in class com.imsl.stat.ANOVA: Returns the estimated standard deviation of the model error.
getModelMeanSquare() - Method in class com.imsl.stat.ANOVA: Returns the model mean square.
getMonthBasis() - Method in class com.imsl.finance.DayCountBasis: Returns the (days in month) portion of the Day Count Basis.
getMRBar() - Method in class com.imsl.chart.qc.XmR: Returns the expected mean of of all of the moving ranges of two observations.
getName() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Name" attribute.
getName() - Method in class com.imsl.io.MPSReader: Returns the name of the MPS problem.
getName() - Method in class com.imsl.io.MPSReader.Row: Returns the name of this row.
getNameBounds() - Method in class com.imsl.io.MPSReader: Returns the name of the BOUNDS set.
getNameColumn(int) - Method in class com.imsl.io.MPSReader: Returns the name of a constraint column.
getNameObjective() - Method in class com.imsl.io.MPSReader: Returns the name of the free row containing the objective.
getNameRanges() - Method in class com.imsl.io.MPSReader: Returns the name of the RANGES set.
getNameRHS() - Method in class com.imsl.io.MPSReader: Returns the name of the RHS section.
getNameRow(int) - Method in class com.imsl.io.MPSReader: Returns the name of a contraint row.
getNCells() - Method in class com.imsl.stat.TableMultiWay.UnbalancedTable: Returns the number of non-empty cells.
getNetwork() - Method in class com.imsl.datamining.neural.BinaryClassification: Returns the network being used for classification.
getNetwork() - Method in class com.imsl.datamining.neural.MultiClassification: Returns the network being used for classification.
getNLost() - Method in class com.imsl.stat.ARSeasonalFit: Returns the number of values in the initial part of the series lost to differencing.
getNMinus() - Method in class com.imsl.chart.qc.CuSumStatus: Returns $N^{-}$ , the number of consecutive periods that the cusums $C_i^{-}$ have been nonzero.
getNode() - Method in class com.imsl.chart.PickEvent: Gets this ChartNode.
getNodes() - Method in class com.imsl.datamining.neural.InputLayer: Return the Perceptrons in the InputLayer.
getNodes() - Method in class com.imsl.datamining.neural.Layer: Return a list of the Perceptrons in this Layer.
getNodes() - Method in class com.imsl.datamining.neural.OutputLayer: Return the Perceptrons in the OutputLayer.
getNormalScores(double[]) - Method in class com.imsl.stat.Ranks: Gets the expected value of normal order statistics (for tied observations, the average of the expected normal scores).
getNotch() - Method in class com.imsl.chart.BoxPlot: Gets the "Notch" attribute value.
getNPlus() - Method in class com.imsl.chart.qc.CuSumStatus: Returns $N^{+}$ , the number of consecutive periods that the cusums $C_i^{+}$ have been nonzero.
getNRowsMissing() - Method in class com.imsl.stat.CategoricalGenLinModel: Returns the number of rows of data in x that contain missing values in one or more specific columns of x.
getNRowsMissing() - Method in class com.imsl.stat.DiscriminantAnalysis: Returns the number of rows of data encountered containing missing values (NaN).
getNTimes() - Static method in class com.imsl.stat.KaplanMeierECDF: Retrieves the number of points in the empirical CDF
getNumber() - Method in class com.imsl.chart.AbstractChartNode: Returns the value of the "Number" attribute.
getNumberFormat() - Method in class com.imsl.math.PrintMatrixFormat: Returns the NumberFormat to be used in formatting double and Complex entries.
getNumberGridPointsX() - Method in class com.imsl.chart3d.Surface: Returns the value of the "NumberGridPointsX" attribute.
getNumberGridPointsY() - Method in class com.imsl.chart3d.Surface: Returns the value of the "NumberGridPointsY" attribute.
getNumberMissing() - Method in class com.imsl.stat.ARMAEstimateMissing: Returns the number of missing values in the original series
getNumberMissing() - Method in class com.imsl.stat.KolmogorovOneSample: Returns the number of missing values in the data.
getNumberMissingX() - Method in class com.imsl.stat.KolmogorovTwoSample: Returns the number of missing values in the x sample.
getNumberMissingY() - Method in class com.imsl.stat.KolmogorovTwoSample: Returns the number of missing values in the y sample.
getNumberObservations() - Method in class com.imsl.chart.BoxPlot.Statistics: Returns the number of observations.
getNumberOfBackcasts() - Method in class com.imsl.stat.ARMA: Returns the number of backcasts used to calculate the AR coefficients for the time series z.
getNumberOfBinaryConstraints() - Method in class com.imsl.io.MPSReader: Returns the number of binary constraints.
getNumberOfClasses() - Method in class com.imsl.datamining.neural.UnsupervisedNominalFilter: Retrieves the number of classes in the nominal variable.
getNumberOfClasses() - Method in class com.imsl.datamining.neural.UnsupervisedOrdinalFilter: Retrieves the number of categories associated with this ordinal variable.
getNumberOfColumns() - Method in class com.imsl.io.MPSReader: Returns the number of columns in the constraint matrix.
getNumberOfColumns() - Method in class com.imsl.math.ComplexSparseMatrix: Returns the number of columns in the matrix.
getNumberOfColumns() - Method in class com.imsl.math.SparseMatrix: Returns the number of columns in the matrix.
getNumberOfEpochs() - Method in class com.imsl.datamining.neural.EpochTrainer: Returns the number of epochs used during stage I training.
getNumberOfInputs() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the number of inputs to the Network.
getNumberOfInputs() - Method in class com.imsl.datamining.neural.Network: Returns the number of Network inputs.
getNumberOfIntegerConstraints() - Method in class com.imsl.io.MPSReader: Returns the number of integer constraints.
getNumberOfLinks() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the number of Links in the Network.
getNumberOfLinks() - Method in class com.imsl.datamining.neural.Network: Returns the number of Network Links among the nodes.
getNumberOfMissingRows() - Method in class com.imsl.stat.RegressorsForGLM: Returns the number of rows in the regressors matrix containing NaN (not a number).
getNumberOfNonZeros() - Method in class com.imsl.io.MPSReader: Returns the number of nonzeros in the constraint matrix.
getNumberOfNonZeros() - Method in class com.imsl.io.MPSReader.Row: Returns the number of nonzero elements in this row.
getNumberOfNonzeros() - Method in class com.imsl.math.ComplexSparseCholesky: Returns the number of nonzeros in the Cholesky factor.
getNumberOfNonZeros() - Method in class com.imsl.math.ComplexSparseMatrix: Returns the number of nonzeros in the matrix.
getNumberOfNonzeros() - Method in class com.imsl.math.SparseCholesky: Returns the number of nonzeros in the Cholesky factor.
getNumberOfNonZeros() - Method in class com.imsl.math.SparseMatrix: Returns the number of nonzeros in the matrix.
getNumberOfOutputs() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the number of outputs from the Network.
getNumberOfOutputs() - Method in class com.imsl.datamining.neural.Network: Returns the number of Network output Perceptrons.
getNumberOfRegressors() - Method in class com.imsl.stat.RegressorsForGLM: Returns the number regressors.
getNumberOfRows() - Method in class com.imsl.io.MPSReader: Returns the number of rows in the constraint matrix.
getNumberOfRows() - Method in class com.imsl.math.ComplexSparseMatrix: Returns the number of rows in the matrix.
getNumberOfRows() - Method in class com.imsl.math.SparseMatrix: Returns the number of rows in the matrix.
getNumberOfThreads() - Method in class com.imsl.datamining.neural.EpochTrainer: Gets the number of threads to use during stage I training.
getNumberOfTies() - Method in class com.imsl.stat.KolmogorovOneSample: Returns the number of ties in the data.
getNumberOfWeights() - Method in class com.imsl.datamining.neural.FeedForwardNetwork: Returns the number of weights in the Network.
getNumberOfWeights() - Method in class com.imsl.datamining.neural.Network: Returns the number of weights in the Network.
getNumericFactor() - Method in class com.imsl.math.ComplexSparseCholesky: Returns the numeric Cholesky factor.
getNumericFactor() - Method in class com.imsl.math.SparseCholesky: Returns the numeric Cholesky factor.
getNumericFactorizationMethod() - Method in class com.imsl.math.ComplexSparseCholesky: Returns the method used in the numerical factorization of the permuted input matrix.
getNumericFactorizationMethod() - Method in class com.imsl.math.SparseCholesky: Returns the method used in the numerical factorization of the permuted input matrix.
getNumPositiveDev() - Method in class com.imsl.stat.SignTest: Returns the number of positive differences.
getNumRowMissing() - Method in class com.imsl.stat.Covariances: Returns the total number of observations that contain any missing values (Double.NaN).
getNumZeroDev() - Method in class com.imsl.stat.SignTest: Returns the number of zero differences.
getNvalues() - Method in class com.imsl.stat.TableMultiWay.BalancedTable: Returns an array of length nKeys containing in its i-th element (i=0,1,...nKeys-1), the number of levels or categories of the i-th classification variable (column).
getObject(int) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(String) - Method in class com.imsl.io.AbstractFlatFile: Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(int, Map) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(String, Map) - Method in class com.imsl.io.AbstractFlatFile: Returns the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObject(int) - Method in class com.imsl.io.FlatFile: Gets the value of the designated column in the current row of this ResultSet object as an Object in the Java programming language.
getObjective() - Method in class com.imsl.io.MPSReader: Returns the objective as a Row.
getObjectiveCoefficients() - Method in class com.imsl.io.MPSReader: Returns the coefficents of the objective row.
getObjectiveValue() - Method in class com.imsl.math.MinConGenLin: Returns the value of the objective function.
getObservations() - Method in class com.imsl.stat.Covariances: Returns the sum of the frequencies.
getObservationsLost() - Method in class com.imsl.stat.Difference: Returns the number of observations lost because of differencing the time series.
getObservedResponse() - Method in class com.imsl.stat.LinearRegression.CaseStatistics: Returns the observed response for an observation.
getObsPerCluster(int) - Method in class com.imsl.stat.ClusterHierarchical: Returns the number of observations in each cluster.
getOffset() - Method in class com.imsl.chart.Text: Returns the offset.
getOneSidedPValue() - Method in class com.imsl.stat.KolmogorovOneSample: Probability of the statistic exceeding D under the null hypothesis of equality and against the one-sided alternative.
getOneSidedPValue() - Metho