Bayesian meta-elliptical multivariate regression models with fixed marginals on unit intervals

Josemar Rodrigues, Yury R. Benites, Vicente G. Cancho, N. Balakrishnan and Adriano K. Suzuki

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 3, 918-938

Abstract: In this paper, we make use of meta-elliptical copula functions to build a new multivariate distribution with fixed marginal distributions and dependence structure to analyze bounded data. Specifically, we present a flexible p-elliptical multivariate probability distribution in the hypercube (0,1)p p with fixed marginal GF-quantile distributions. We then present some illustrative examples and a meta-elliptical multivariate regression model as a flexible alternative to the multivariate normal regression model on unit intervals. A simulation study and real-life data analysis using a Bayesian framework with the extreme-value quantile functions show the flexibility of the proposed meta-multivariate normal regression model for modeling the observed proportion response variables.

Date: 2023
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DOI: 10.1080/03610926.2021.1933531

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