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.
|Journal||Communications in Statistics: Simulation and Computation|
|Publication status||Published - 2008|
- Fisher's noncentral hypergeometric distribution
- Monte Carlo simulation
- Sampling variate generation
- Wallenius' noncentral hypergeometric distribution