Random Number Generation

UTILITY ROUTINES FOR RANDOM NUMBER GENERATORS

ROUTINE DESCRIPTION
RNOPT Selects the uniform (0,1) multiplicative congruential pseudorandom number generator.
RNOPG Retrieves the indicator of the type of uniform random number generator.
RNSET Initializes a random seed for use in the IMSL random number generators.
RNGET Retrieves the current value of the seed used in the IMSL random number generators.
RNSES Initializes the table in the IMSL random number generators that use shuffling.
RNGES Retrieves the current value of the table in the IMSL random number generators that use shuffling.
RNSEF Retrieves the array used in the IMSL GFSR random number generator.
RNGEF Retrieves the current value of the array used in the IMSL GFSR random number generator.
RNISD Determines a seed that yields a stream beginning 100,000 numbers beyond the beginning of the stream yielded by a given seed used in IMSL multiplicative congruential generators (with no shufflings).
RNIN32 Initializes the 32-bit Mersenne Twister generator using an array.
RNGE32 Retrieves the current table used in the 32-bit Mersenne Twister generator.
RNSE32 Sets the current table used in the 32-bit Mersenne Twister generator.
RNIN64 Initializes the 64-bit Mersenne Twister generator using an array.
RNGE64 Retrieves the current table used in the 64-bit Mersenne Twister generator.
RNSE64 Sets the current table used in the 64-bit Mersenne Twister generator.
 

BASIC UNIFORM DISTRIBUTION

ROUTINE DESCRIPTION
RNUN Selects the uniform (0,1) multiplicative congruential pseudorandom number generator.
RNUNF Retrieves the indicator of the type of uniform random number generator.
 

UNIVARIATE DISCRETE DISTRIBUTIONS

ROUTINE DESCRIPTION
RNBIN Generates pseudorandom numbers from a binomial distribution.
RNGDA Generates pseudorandom numbers from a general discrete distribution using an alias method.
RNGDS Sets up table to generate pseudorandom numbers from a general discrete distribution.
RNGDT Generates pseudorandom numbers from a general discrete distribution using a table lookup method.
RNGEO Generates pseudorandom numbers from a geometric distribution.
RNHYP Generates pseudorandom numbers from a hypergeometric distribution.
RNLGR Generates pseudorandom numbers from a logarithmic distribution.
RNNBN Generates pseudorandom numbers from a negative binomial distribution.
RNPOI Generates pseudorandom numbers from a Poisson distribution.
RNUND Generates pseudorandom numbers from a discrete uniform distribution.
 

UNIVARIATE CONTINUOUS DISTRIBUTIONS

ROUTINE DESCRIPTION
RNBET Generates pseudorandom numbers from a beta distribution.
RNCHI Generates pseudorandom numbers from a chi-squared distribution.
RNCHY Generates pseudorandom numbers from a Cauchy distribution.
RNEXP Generates pseudorandom numbers from a standard exponential distribution.
RNEXV Generates pseudorandom numbers from an extreme value distribution.
RNFDF Generates pseudorandom numbers from the F distribution.
RNEXT Generates pseudorandom numbers from a mixture of two exponential distributions.
RNGAM Generates pseudorandom numbers from a standard gamma distribution.
RNGCS Sets up table to generate pseudorandom numbers from a general continuous distribution.
RNGCT Generates pseudorandom numbers from a general continuous distribution.
RNLNL Generates pseudorandom numbers from a lognormal distribution.
RNNOA Generates pseudorandom numbers from a standard normal distribution using an acceptance/rejection method.
RNNOF Generates a pseudorandom number from a standard normal distribution.
RNNOR Generates pseudorandom numbers from a standard normal distribution using an inverse CDF method.
RNRAL Generates pseudorandom numbers from a Rayleigh distribution.
RNSTA Generates pseudorandom numbers from a stable distribution.
RNSTT Generates pseudorandom numbers from a Student's t distribution.
RNTRI Generates pseudorandom numbers from a triangular distribution on the interval (0, 1).
RNVMS Generates pseudorandom numbers from a von Mises distribution.
RNWIB Generates pseudorandom numbers from a Weibull distribution.
 

MULTIVARIATE DISTRIBUTIONS

ROUTINE DESCRIPTION
RNCOR Generates a pseudorandom orthogonal matrix or a correlation matrix.
RNDAT Generates pseudorandom numbers from a multivariate distribution determined from a given sample.
RNMTN Generates pseudorandom numbers from a multinomial distribution.
RNMVN Generates pseudorandom numbers from a multivariate normal distribution.
RNSPH Generates pseudorandom points on a unit circle or K-dimensional sphere.
RNTAB Generates a pseudorandom two-way table.
RNMVGC Given a Cholesky factorization of a correlation matrix, generates pseudorandom numbers from a Gaussian Copula distribution.
RNMVTC Given a Cholesky factorization of a correlation matrix, generates pseudorandom numbers from a Student's t Copula distribution.
CANCOR Given an input array of deviate values, generates a canonical correlation array.
 

ORDER STATISTICS

ROUTINE DESCRIPTION
RNNOS Generates pseudorandom order statistics from a standard normal distribution.
RNUNO Generates pseudorandom order statistics from a uniform (0, 1) distribution.
 

STOCHASTIC PROCESSES

ROUTINE DESCRIPTION
RNARM Generates a time series from a specified ARMA model.
RNNPP Generates pseudorandom numbers from a nonhomogenous Poisson process.
 

SAMPLES AND PERMUTATIONS

ROUTINE DESCRIPTION
RNPER Generates a pseudorandom permutation.
RNSRI Generates a simple pseudorandom sample of indices.
RNSRS Generates a simple pseudorandom sample from a finite population.
 

LOW DISCREPANCY SEQUENCES

ROUTINE DESCRIPTION
FAURE_FREE Frees the structure containing information about the Faure sequence.
FAURE_INIT Shuffled Faure sequence initialization.
FAURE_NEXT Shuffled Faure sequence initialization.