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Extensions of the multivariate Birnbaum-Saunders distribution and its associated regression models

Grant number: 22/06421-7
Support Opportunities:Scholarships abroad - Research
Effective date (Start): September 17, 2022
Effective date (End): November 14, 2022
Field of knowledge:Physical Sciences and Mathematics - Probability and Statistics - Statistics
Principal Investigator:Filidor Edilfonso Vilca Labra
Grantee:Filidor Edilfonso Vilca Labra
Host Investigator: Narayanaswamy Balakrishnan
Host Institution: Instituto de Matemática, Estatística e Computação Científica (IMECC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Research place: McMaster University, Canada  

Abstract

The goal of this project is to present a study of estimation and diagnostic analysis for the multivariate log- Birnbaum-Saunders regression models based on {\it scale mixture of skew-normal distributions} (SMSN) (Branco and Dey, 2001): We first will consider a estimation study based on the modified moment method for multivariate Birnbaum-Saunders distributions (based on the symmetric SMSN distribution). Next, a multivariate log- Birnbaum-Saunders regression model will be proposed based on the SMSN distribution, which is a multivariate extension of the log- Birnbaum-Saunders regression models proposed by Rieck and Nedelman (1991) and Romeiro et al. (2020). Estimation and diagnostic analysis Cook, 1986; Zu and Lee, 2001) will be developed for the proposed regression model; see more details at the end of manuscript. The maximum likelihood estimates will be obtained by an EM algorithm. This regression model extends the results of Romeiro et al. (2020). (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
VILCA, FILIDOR; ZELLER, CAMILA BORELLI; BALAKRISHNAN, NARAYANASWAMY. Multivariate Birnbaum-Saunders distribution based on a skewed distribution and associated EM-estimation. BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS, v. 37, n. 1, p. 29-pg., . (22/06421-7, 20/16713-0)

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