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

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    Abstract

    Several methods for generating variates with univariate and multivariate Wallenius' 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 tau 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.
    Original languageEnglish
    JournalCommunications in Statistics: Simulation and Computation
    Volume37
    Issue number2
    Pages (from-to)241-257
    ISSN0361-0918
    DOIs
    Publication statusPublished - 2008

    Keywords

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

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