### Abstract

We describe an algorithm for the sequential sampling of entries in multi-way contingency tables with given constraints. The algorithm can be used for computations in exact conditional inference. To justify the algorithm, a theory relates sampling values at each step to properties of the associated toric ideal using computational commutative algebra. In particular, the property of interval cell counts at each step is related to exponents on lead indeterminates of a lexicographic Gröbner basis. Also, the approximation of integer programming by linear programming for sampling is related to initial terms of a toric ideal. We apply the algorithm to examples of contingency tables which appear in the social and medical sciences. The numerical results demonstrate that the theory is applicable and that the algorithm performs well.

Original language | English (US) |
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Pages (from-to) | 523-545 |

Number of pages | 23 |

Journal | Annals of Statistics |

Volume | 34 |

Issue number | 1 |

DOIs | |

State | Published - Feb 1 2006 |

### Keywords

- Conditional inference
- Contingency table
- Exact test
- Monte Carlo
- Sequential importance sampling
- Toric ideal

### ASJC Scopus subject areas

- Statistics and Probability
- Statistics, Probability and Uncertainty

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## Cite this

*Annals of Statistics*,

*34*(1), 523-545. https://doi.org/10.1214/009053605000000822