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February 1998 Algebraic algorithms for sampling from conditional distributions
Persi Diaconis, Bernd Sturmfels
Ann. Statist. 26(1): 363-397 (February 1998). DOI: 10.1214/aos/1030563990

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.

Citation

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Persi Diaconis. Bernd Sturmfels. "Algebraic algorithms for sampling from conditional distributions." Ann. Statist. 26 (1) 363 - 397, February 1998. https://doi.org/10.1214/aos/1030563990

Information

Published: February 1998
First available in Project Euclid: 28 August 2002

zbMATH: 0952.62088
MathSciNet: MR1608156
Digital Object Identifier: 10.1214/aos/1030563990

Subjects:
Primary: 13P10 , 6E17

Keywords: conditional inference , exponential families , Gröbner bases , Monte Carlo Markov chain

Rights: Copyright © 1998 Institute of Mathematical Statistics

Vol.26 • No. 1 • February 1998
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