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.
CITATION STYLE
Diaconis, P., & Sturmfels, B. (1998). Algebraic algorithms for sampling from conditional distributions. Annals of Statistics, 26(1), 363–397. https://doi.org/10.1214/aos/1030563990
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