Algebraic algorithms for sampling from conditional distributions
Persi DiaconisBernd SturmfelsCornell University and University of California, Berkeley
1998en
ABI
Abstract
We construct Markov chain algorithms for sampling from discrete exponential families conditional on a sufficient statistic. Examples include contingency tables, logistic regression, and spectral analysis of permutation data. The algorithms involve computations in polynomial rings using Gröbner bases.
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Cited by 20 references