Minimum information dependence modeling

Tomonari Sei; Keisuke Yano

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arXiv · 2206.06792

Minimum information dependence modeling

Tomonari Sei·Keisuke Yano

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Abstract

We propose a method to construct a joint statistical model for mixed-domain data to analyze their dependence. Multivariate Gaussian and log-linear models are particular examples of the proposed model. It is shown that the functional equation defining the model has a unique solution under fairly weak conditions. The model is characterized by two orthogonal parameters: the dependence parameter and the marginal parameter. To estimate the dependence parameter, a conditional inference together with a sampling procedure is proposed and is shown to provide a consistent estimator. Illustrative examples of data analyses involving penguins and earthquakes are presented.

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Tomonari Sei, Keisuke Yano. 2022-06-14. Minimum information dependence modeling. https://arxiv.org/abs/2206.06792

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