Factor analysis for a mixture of continuous and binary random variables
Methodology
2023-02-14 v2 Data Analysis, Statistics and Probability
Abstract
We propose a multivariate probability distribution that models a linear correlation between binary and continuous variables. The proposed distribution is a natural extension of the previously developed multivariate binary distribution. As an application of the proposed distribution, we develop a factor analysis for a mixture of continuous and binary variables. We also discuss improper solutions associated with factor analysis. As a prescription to avoid improper solutions, we propose a constraint that each row vector of factor loading matrix has the same norm. We numerically validated the proposed factor analysis and norm constraint prescription by analyzing real datasets.
Cite
@article{arxiv.2209.12147,
title = {Factor analysis for a mixture of continuous and binary random variables},
author = {Takashi Arai},
journal= {arXiv preprint arXiv:2209.12147},
year = {2023}
}
Comments
34 pages, 4 figures, minor modifications