Perfect sampling algorithm for small m×n contingency tables
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A Markov chain is proposed that uses coupling from the past sampling algorithm for sampling m×n contingency tables. This method is an extension of the one proposed by Kijima and Matsui (Rand. Struct. Alg., 29:243–256, 2006). It is not polynomial, as it is based upon a recursion, and includes a rejection phase but can be used for practical purposes on small contingency tables as illustrated in a classical 4×4 example.
KeywordsMarkov chains Perfect sampling Contingency tables Coupling from the past
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- Cryan, M., Dyer, M., Goldberg, L.A., Jerrum, M., Martin, R.: Rapidly mixing Markov chains for sampling contingency tables with constant number of rows. In: Proceedings of the 43rd Annual Symposium on Foundations of Computer Science (FOCS 2002), pp. 711–720 (2002) Google Scholar
- Diaconis, P., Saloff-Coste, L.: Random walk on contingency tables with fixed row and column sums. Technical report, Department of Mathematics, Harvard University (1995) Google Scholar