Sampling Methods for Wallenius' and Fisher's Noncentral Hypergeometric Distributions

Abstract

Several methods for generating variates with univariate and multivariate Walleniu' and Fisher's noncentral hypergeometric distributions are developed. Methods for the univariate distributions include: simulation of urn experiments, inversion by binary search, inversion by chop-down search from the mode, ratio-of-uniforms rejection method, and rejection by sampling in the τ domain. Methods for the multivariate distributions include: simulation of urn experiments, conditional method, Gibbs sampling, and Metropolis-Hastings sampling. These methods are useful for Monte Carlo simulation of models of biased sampling and models of evolution and for calculating moments and quantiles of the distributions.

Keywords:

• Fisher's noncentral hypergeometric distribution
• Monte Carlo simulation
• Sampling
• variate generation
• Walleniu' noncentral hypergeometric distribution

Mathematics Subject Classification:

• 62D05
• 62E15
• 62H10
• 65C05
• 65C60
• 92D15