Dependence properties of multivariate distributions with proportional hazard rate marginals
APPLIED MATHEMATICAL MODELLING, vol.77, pp.182-198, 2020 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 77
- Publication Date: 2020
- Doi Number: 10.1016/j.apm.2019.07.030
- Journal Name: APPLIED MATHEMATICAL MODELLING
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, INSPEC, Metadex, Pollution Abstracts, Sociological abstracts, zbMATH, Civil Engineering Abstracts
- Page Numbers: pp.182-198
- Keywords: Copula, Dependence property, Maximum likelihood estimator, Trivariate Kendall's tau, Trivariate inverse generalized distribution
- Çukurova University Affiliated: Yes
Abstract
In this paper, we introduce a new family of multivariate distributions, so called the multivariate proportional hazard rate family of distributions and study its properties. We derive multivariate dependence properties based on a survival function and based on a survival copula function. Multivariate dependence properties based on a survival function are given by multivariate total positivity of order 2, right corner set increasing, smaller in lower or-thant order and right tail increasing. Multivariate dependence properties based on a survival copula function are some coefficients of concordance. The survival copula function is used to model this family of multivariate distributions. We illustrate capability of the introduced model on a real data set related to the level of thyroid hormone. (C) 2019 Elsevier Inc. All rights reserved.