A broad class of multivariate distributions for rates and proportions

This paper introduces a general class of multivariate distributions for rates and proportions on the basis of the multivariate elliptical distribution. We derive various general properties of this multivariate distribution. The model parameters are estimated using the maximum likelihood estimation method. In particular, we have considered parameter estimation in detail for two special cases of this multivariate family, using multivariate normal kernel and multivariate Student-tkernel. Hypothesis testing inference for the correlation matrix on the basis of the likelihood ratio test statistic is also proposed. Empirical applications that employ real data are considered to illustrate the usefulness of the new class of multivariate distributions for rates and proportions in practice. (C) 2022 Elsevier Inc. All rights reserved.

Automated summary

This paper introduces a general class of multivariate distributions based on the multivariate elliptical distribution, which is applied to rates and proportions estimation. The model parameters are estimated using the maximum likelihood estimation method, and parameter estimation methods for two special cases of this multivariate family are discussed in detail. In addition, a hypothesis testing method for the correlation matrix based on the likelihood ratio test statistic is proposed. Empirical applications using real data are considered to demonstrate the usefulness of this new class of multivariate distributions for rates and proportions in practice.