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Abstract
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The holonomic gradient method gives an algorithm to efficiently and accurately
evaluate normalizing constants and their derivatives. We apply the holonomic
gradient method in the case of the conditional Poisson or multinomial distribution on
two-way contingency tables. We utilize the modular method in computer algebra or
some other tricks for an efficient and exact evaluation, and we compare them and
discuss on their implementation. We also discuss on a theoretical aspect of the
distribution from the viewpoint of the conditional maximum likelihood estimation.
We decompose parameters of interest and nuisance parameters in terms of
sigma algebras for general two-way contingency tables with arbitrary zero cell
patterns.
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Keywords
holonomic gradient method, two-way contingency tables,
modular method, conditional maximum likelihood estimation
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Mathematical Subject Classification 2010
Primary: 33C90, 65Q10, 62B05, 62H17
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Milestones
Received: 14 June 2018
Revised: 5 January 2020
Accepted: 24 March 2020
Published: 28 December 2020
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