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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A bivariate Birnbaum-Saunders regression model

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Author(s):
Vilca, Filidor [1] ; Romeiro, Renata G. [1] ; Balakrishnan, N. [2]
Total Authors: 3
Affiliation:
[1] Univ Estadual Campinas, Dept Estat, Caixa Postal 6065, Sao Paulo, SP - Brazil
[2] McMaster Univ, Dept Math & Stat, Hamilton, ON - Canada
Total Affiliations: 2
Document type: Journal article
Source: COMPUTATIONAL STATISTICS & DATA ANALYSIS; v. 97, p. 169-183, MAY 2016.
Web of Science Citations: 6
Abstract

In this work, we propose a bivariate Birnbaum-Saunders regression model through the use of bivariate Sinh-normal distribution. The proposed regression model has its marginal as the Birnbaum-Saunders regression model of Rieck and Nedelman (1991), which has been discussed extensively by various authors with natural applications in survival and reliability studies. This bivariate regression model can be used to analyze correlated log lifetimes of two units, in which the dependence structure between observations arises from the bivariate normal distribution. The main aim of this paper is to propose a bivariate Birnbaum-Saunders regression model and discuss some of its properties. Specifically, we have developed the moment estimation, the maximum likelihood estimation and the observed Fisher information matrix. Hypothesis testing is also performed by the use of the asymptotic normality of the maximum-likelihood estimators. Finally, the results of simulation studies as well as an application to a real data set are presented to illustrate the model and all the inferential methods developed here. (C) 2015 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 11/06263-8 - Inference and diagnostic in Birnbaum-saunders models based on scale mixture Skew-normal distribution
Grantee:Filidor Edilfonso Vilca Labra
Support Opportunities: Scholarships abroad - Research