| UnivRNG-package {UnivRNG} | R Documentation |
Univariate Pseudo-Random Number Generation
Description
This package implements the algorithms described in Demirtas (2005) for pseudo-random number generation of 17 univariate distributions. The following distributions are available: Left Truncated Gamma, Laplace, Inverse Gaussian, Von Mises, Zeta (Zipf), Logarithmic, Beta-Binomial, Rayleigh, Pareto, Non-central t, Non-central Chi-squared, Doubly non-central F, Standard t, Weibull, Gamma with \alpha<1, Gamma with \alpha>1, and Beta with \alpha<1 and \beta<1. For some distributions, functions that have similar capabilities exist in the base package; the functions herein should be regarded as complementary tools.
The methodology for each random-number generation procedure varies and each distribution has its own function. draw.left.truncated.gamma, draw.von.mises, draw.inverse.gaussian, draw.zeta, draw.gamma.alpha.less.than.one, and draw.beta.alphabeta.less.than.one are based on acceptance/rejection region techniques. draw.rayleigh, draw.pareto, and draw.weibull utilize the inverse CDF method. The chop-down method is used for draw.logarithmic. In draw.laplace, a sample from an exponential distribution with mean 1/\lambda is generated and subsequently the sign is changed with probability 0.5 and all variables are shifted by \alpha. For the Beta-Binomial distribution in draw.beta.binomial, \pi is generated as the appropriate \beta and used as the success probability for the binomial portion. draw.noncentral.t utilizes on arithmetic functions of normal and chi-squared random variables. draw.noncentral.chisquared is based on the sum of squared random normal variables, and draw.noncentral.F is a ratio of chi-squared random variables generated via draw.noncentral.chisquared. draw.t employs a rejection polar method developed by Bailey (1994). draw.gamma.alpha.greater.than.one uses a ratio of uniforms method by Cheng and Feast (1979).
Details
| Package: | UnivRNG |
| Type: | Package |
| Version: | 1.2.3 |
| Date: | 2021-03-05 |
| License: | GPL-2 | GPL-3 |
Author(s)
Hakan Demirtas, Rawan Allozi, Ran Gao
Maintainer: Ran Gao <rgao8@uic.edu>
References
Bailey, R. W. (1994). Polar generation of random variates with the t-distribution. Mathematics of Computation, 62, 779-781.
Cheng, R. C. H., & Feast, G. M. (1979). Some simple gamma variate generation. Applied Statistics, 28, 290-295.
Demirtas, H. (2005). Pseudo-random number generation in R for some univariate distributions. Journal of Modern Applied Statistical Methods, 4(1), 300-311.