A class of statistical models to weaken independence in two-way contingency tables

Details A class of statistical models to weaken independence in two-way contingency tables A class of statistical models to weaken independence in two-way contingency tables

2008-03-11

arxiv.org/abs/0803.1582v2

Mathematics

Statistics Theory

A theorem has been removed because of a gap in the proof. Minor style changes

Scientific paper

In this paper we study a new class of statistical models for contingency tables. We define this class of models through a subset of the binomial equations of the classical independence model. We use some notions from Algebraic Statistics to compute their sufficient statistic, and to prove that they are log-linear. Moreover, we show how to compute maximum likelihood estimates and to perform exact inference through the Diaconis-Sturmfels algorithm. Examples show that these models can be useful in a wide range of applications.

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