Bivariate Proportional Hazard Models: Structure and Inference

被引：2

作者：

Arnold, Barry C. ^{[1
]}

Martinez-Florez, Guillermo ^{[2
]}

Gomez, Hector W. ^{[3
]}

机构：

[1] Univ Calif Riverside, Stat Dept, Riverside, CA 92521 USA

[2] Univ Cordoba, Fac Ciencias, Dept Matemat & Estadist, Cordoba 2300, Colombia

[3] Univ Antofagasta, Fac Ciencias Basicas, Dept Matemat, Antofagasta 1240000, Chile

来源：

SYMMETRY-BASEL | 2022年 / 14卷 / 10期

关键词：

bivariate exponential models; conditional specification; gumbel distribution; dependent lifetime data; functional equation; DISTRIBUTIONS;

D O I：

10.3390/sym14102073

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

We focus on a variety of bivariate models with proportional hazard components. Models with proportional hazard marginals are described together with a selection of models with proportional hazard conditional distributions. The bivariate distributions with marginal proportional hazards distributions are shown to be closely related to certain known bivariate exponential models. Two distinct kinds of conditional specification are investigated. Discussion is provided of cases with hazard function components that are (1) completely unknown, (2) known to belong to given parametric families and (3) completely known. Since the models are designed for use with survival data, it is inevitable that the marginal and conditional distributions will be asymmetric. However, logarithmic transformations in some cases will result in symmetric component distributions.

引用

页数：12

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