Routines

Appendix B: Alphabetical Summary of Routines

Routines

[A] [B] [C] [D] [E] [F] [G] [H] [ I ] [J] [K] [L] [M]
[N] [O] [P] [Q] [R] [S] [T] [U] [V] [W] [X] [Y] [Z]

Function Purpose Statement

anova_balanced	Analyzes a balanced complete experimental design for a fixed, random, or mixed model.
anova_factorial	Analyzes a balanced factorial design with fixed effects.
anova_nested	Analyzes a completely nested random model with possibly unequal numbers in the subgroups.
anova_oneway	Analyzes a one-way classification model.
arma	Computes least-square estimates of parameters for an ARMA model.
arma_forecast	Computes forecasts and their associated probability limits for an ARMA model.
autocorrelation	Computes the sample autocorrelation function of a stationary time series.
auto_arima	Automatically identifies time series outliers, determines parameters of a multiplicative seasonal ARIMA model and produces forecasts that incorporate the effects of outliers whose effects persist beyond the end of the series
auto_uni_ar	Automatic selection and fitting of a univariate autoregressive time series model.

beta	Evaluates the complete beta function.
beta_cdf	Evaluates the beta probability distribution function.
beta_incomplete	Evaluates the real incomplete beta function.
beta_inverse_cdf	Evaluates the inverse of the beta distribution function.
binomial_cdf	Evaluates the binomial distribution function.
binomial_coefficient	Evaluates the binomial coefficient.
binomial_pdf	Evaluates the binomial probability function.
bivariate_normal_cdf	Evaluates the bivariate normal distribution function.
box_cox_transform	Performs a Box-Cox transformation.

categorical_glm	Analyzes categorical data using logistic, Probit, Poisson, and other generalized linear models.
chi_squared_cdf	Evaluates the chi-squared distribution function.
chi_squared_inverse_cdf	Evaluates the inverse of the chi-squared distribution function.
chi_squared_test	Performs a chi-squared goodness-of-fit test.
cluster_hierarchical	Performs a hierarchical cluster analysis given a distance matrix.
cluster_k_means	Performs a K-means (centroid) cluster analysis.
cluster_number	Computes cluster membership for a hierarchical cluster tree.
cochran_q_test	Performs a Cochran Q test for related observations.
contingency_table	Performs a chi-squared analysis of a two-way contingency table.
continuous_table_setup	Sets up table to generate pseudorandom numbers from a general continuous distribution.
covariances	Computes the sample variance-covariance or correlation matrix.
cox_stuart_trends_test	Performs the Cox and Stuart’ sign test for trends in location and dispersion.
crd_factorial	Analyzes data from balanced and unbalanced completely randomized experiments.
crosscorrelation	Computes the sample cross-correlation function of two stationary time series

data_sets	Retrieves a commonly analyzed data set.
difference	Differences a seasonal or nonseasonal time series.
discrete_table_setup	Sets up a table to generate pseudorandom numbers from a general discrete distribution.
discriminant_analysis	Performs discriminant function analysis.

error_code	Returns the code corresponding to the error message from the last function called.
error_options	Sets various error handling options.
estimate_missing	Estimates missing values in a time series.
exact_enumeration	Computes exact probabilities in a two-way contingency table, using the total enumeration method.
exact_network	Computes exact probabilities in a two-way contingency table using the network algorithm.

factor_analysis	Extracts initial factor-loading estimates in factor analysis.
faure_next_point	Computes a shuffled Faure sequence
friedmans_test	Performs Friedman’s test for a randomized complete block design.

gamma	Evaluates the real gamma functions.
gamma_cdf	Evaluates the gamma distribution function.
gamma_incomplete	Evaluates the incomplete gamma function.
gamma_inverse_cdf	Evaluates the inverse of the gamma distribution function.
garch	Computes estimates of the parameters of a GARCH (p, q) model

homogeneity	Conducts Bartlett’s and Levene’s tests of the homogeneity of variance assumption in analysis of variance.
hypergeometric_cdf	Evaluates the hypergeometric distribution function.
hypergeometric_pdf	Evaluates the hypergeometric probability function.
hypothesis_partial	Constructs a completely testable hypothesis.
hypothesis_scph	Sums of cross products for a multivariate hypothesis.
hypothesis_test	Tests for the multivariate linear hypothesis.

kalman	Performs Kalman filtering and evaluates the likelihood function for the state-space model.
kaplan_meier_estimates	Computes Kaplan-Meier estimates of survival probabilities in stratified samples.
kolmogorov_one	Performs a Kolmogorov-Smirnov’s one-sample test for continuos distributions.
kolmogorov_two	Performs a Kolmogorov-Smirnov’s two-sample test
kruskal_wallis_test	Performs a Kruskal-Wallis’s test for identical population medians.
k_trends_test	Performs k-sample trends test against ordered alternatives.

lack_of_fit	Performs lack-of-fit test for an univariate time series or transfer function given the appropriate correlation function.
latin_square	Analyzes data from latin-square experiments.
lattice	Analyzes balanced and partially-balanced lattice experiments.
life_tables	Produces population and cohort life tables.
Lnorm_regression	Fits a multiple linear regression model using criteria other than least squares.
log_beta	Evaluates the log of the real beta function.
log_gamma	Evaluates the logarithm of the absolute value of the gamma function.

machine (float)	Returns information describing the computer's floating-point arithmetic.
machine (integer)	Returns integer information describing the computer's arithmetic.
mat_mul_rect	Computes the transpose of a matrix, a matrix-vector product, a matrix-matrix product, a bilinear form, or any triple product.
max_arma	Exact maximum likelihood estimation of the parameters in a univariate ARMA (autoregressive, moving average) time series model.
mlff_network	Creates a multilayered feedforward neural network.
mlff_network_forecast	Calculates forecasts for trained multilayered feedforward neural networks.
mlff_network_trainer	Trains a multilayered feedforward neural network.
multi_crosscorrelation	Computes the multichannel cross-correlation function of two mutually stationary multichannel time series.
multiple_comparisons	Performs Student-Newman-Keuls multiple comparisons test.
multivar_normality_test	Computes Mardia’s multivariate measures of skewness and kurtosis and tests for multivariate normality.

noether_cyclical_trend	Performs the Noether’s test for cyclical trend.
non_central_chi_sq	Evaluates the noncentral chi-squared distribution function.
non_central_chi_sq_inv	Evaluates the inverse of the noncentral chi-squared function.
non_central_t_cdf	Evaluates the noncentral Student’s t distribution function.
non_central_t_inv_cdf	Evaluates the inverse of the noncentral Student’s t distribution function.
nonlinear_optimization	Fits a nonlinear regression model using Powell's algorithm.
nonlinear_regression	Fits a nonlinear regression model.
nonparam_hazard_rate	Performs nonparametric hazard rate estimation using kernel functions and quasi-likelihoods.
normal_cdf	Evaluates the standard normal (Gaussian) distribution function.
normal_inverse_cdf	Evaluates the inverse of the standard normal (Gaussian) distribution function.
normal_one_sample	Computes statistics for mean and variance inferences using a sample from a normal population.
normal_two_sample	Computes statistics for mean and variance inferences using samples from two normal population.
normality_test	Performs a test for normality.

output_file

Sets the output file or the error message output file.

page	Sets or retrieves the page width or length.
partial_autocorrelation	Computes the sample partial autocorrelation function of a stationary time series.
partial_covariances	Computes partial covariances or partial correlations from the covariance or correlation matrix.
permute_matrix	Permutes the rows or columns of a matrix.
permute_vector	Rearranges the elements of a vector as specified by a permutation.
poisson_cdf	Evaluates the Poisson distribution function.
poisson_pdf	Evaluates the Poisson probability function.
poly_prediction	Computes predicted values, confidence intervals, and diagnostics after fitting a polynomial regression model.
poly_regression	Performs a polynomial least-squares regression.
pooled_covariances	Computes a pooled variance-covariance from the observations.
principal_components	Computes principal components.
prop_hazards_gen_lin	Analyzes time event data via the proportional hazards model.

random_arma	Generates pseudorandom ARMA process numbers.
random_beta	Generates pseudorandom numbers from a beta distribution.
random_binomial	Generates pseudorandom binomial numbers.
random_cauchy	Generates pseudorandom numbers from a Cauchy distribution.
random_chi_squared	Generates pseudorandom numbers from a chi-squared distribution.
random_exponential	Generates pseudorandom numbers from a standard exponential distribution.
random_exponential_mix	Generates pseudorandom mixed numbers from a standard exponential distribution.
random_gamma	Generates pseudorandom numbers from a standard gamma distribution.
random_general_continuous	Generates pseudorandom numbers from a general continuous distribution.
random_general_discrete	Generates pseudorandom numbers from a general discrete distribution using an alias method or optionally a table lookup method.
random_geometric	Generates pseudorandom numbers from a geometric distribution.
random_GFSR_table_get	Retrieves the current table used in the GFSR generator.
random_GFSR_table_set	Sets the current table used in the GFSR generator.
random_hypergeometric	Generates pseudorandom numbers from a hypergeometric distribution.
random_logarithmic	Generates pseudorandom numbers from a logarithmic distribution.
random_lognormal	Generates pseudorandom numbers from a lognormal distribution.
random_MT32_init	Initializes the 32-bit Mersenne Twister generator using an array.
random_MT32_table_get	Retrieves the current table used in the 32-bit Mersenne Twister generator.
random_MT32_table_set	Sets the current table used in the 32-bit Mersenne Twister generator.
random_MT64_init	Initializes the 64-bit Mersenne Twister generator using an array.
random_MT64_table_get	Retrieves the current table used in the 64-bit Mersenne Twister generator.
random_MT64_table_set	Sets the current table used in the 64-bit Mersenne Twister generator.
random_multinomial	Generates pseudorandom numbers from a multinomial distribution.
random_mvar_from_data	Generates pseudorandom numbers from a multivariate distribution determined from a given sample.
random_neg_binomial	Generates pseudorandom numbers from a negative binomial distribution.
random_normal	Generates pseudorandom numbers from a standard normal distribution using an inverse CDF method.
random_normal_multivariate	Generates pseudorandom numbers from a multivariate normal distribution.
random_npp	Generates pseudorandom numbers from a nonhomogeneous Poisson process.
random_option	Selects the uniform (0, 1) multiplicative congruential pseudorandom number generator.
random_option_get	Retrieves the uniform (0, 1) multiplicative congruential pseudorandom number generator.
random_order_normal	Generates pseudorandom order statistics from a standard normal distribution.
random_order_uniform	Generates pseudorandom order statistics from a uniform (0, 1) distribution
random_orthogonal_matrix	Generates a pseudorandom orthogonal matrix or a correlation matrix.
random_permutation	Generates a pseudorandom permutation.
random_poisson	Generates pseudorandom numbers from a Poisson distribution.
random_sample	Generates a simple pseudorandom sample from a finite population.
random_sample_indices	Generates a simple pseudorandom sample of indices.
random_seed_get	Retrieves the current value of the seed used in the IMSL random number generators.
random_seed_set	Initializes a random seed for use in the IMSL random number generators.
random_sphere	Generates pseudorandom points on a unit circle or K-dimensional sphere.
random_stable	Sets up a table to generate pseudorandom numbers from a general discrete distribution.
random_student_t	Generates pseudorandom Student's t.
random_substream_seed_get	Retrieves a seed for the congruential generators that do not do shuffling that will generate random numbers beginning 100,000 numbers farther along.
random_table_get	Retrieves the current table used in the shuffled generator.
random_table_set	Sets the current table used in the shuffled generator.
random_table_twoway	Generates a pseudorandom two-way table.
random_triangular	Generates pseudorandom numbers from a triangular distribution.
random_uniform	Generates pseudorandom numbers from a uniform (0, 1) distribution.
random_uniform_discrete	Generates pseudorandom numbers from a discrete uniform distribution.
random_von_mises	Generates pseudorandom numbers from a von Mises distribution.
random_weibull	Generates pseudorandom numbers from a Weibull distribution.
randomness_test	Performs a test for randomness.
ranks	Computes the ranks, normal scores, or exponential scores for a vector of observations.
rcbd_factorial	Analyzes data from balanced and unbalanced randomized complete-block experiments.
regression	Fits a multiple linear regression model using least squares.
regression_prediction	Computes predicted values, confidence intervals, and diagnostics after fitting a regression model.
regression_selection	Selects the best multiple linear regression models.
regression_stepwise	Builds multiple linear regression models using forward selection, backward selection or stepwise selection.
regression_summary	Produces summary statistics for a regression model given the information from the fit.
regressors_for_glm	Generates regressors for a general linear model.
robust_covariances	Computes a robust estimate of a covariance matrix and mean vector.
random_arma	Generates pseudorandom ARMA process numbers.
random_beta	Generates pseudorandom numbers from a beta distribution.
random_binomial	Generates pseudorandom binomial numbers.
random_cauchy	Generates pseudorandom numbers from a Cauchy distribution.
random_chi_squared	Generates pseudorandom numbers from a chi-squared distribution.
random_exponential	Generates pseudorandom numbers from a standard exponential distribution.
random_exponential_mix