Minimum information dependence modeling
Methodology
2023-10-03 v4
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.
Keywords
Cite
@article{arxiv.2206.06792,
title = {Minimum information dependence modeling},
author = {Tomonari Sei and Keisuke Yano},
journal= {arXiv preprint arXiv:2206.06792},
year = {2023}
}
Comments
41 pages, 3 figures