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Multivariate Birnbaum-Saunders distribution based on a skewed distribution and associated EM-estimation

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Author(s):
Vilca, Filidor ; Zeller, Camila Borelli ; Balakrishnan, Narayanaswamy
Total Authors: 3
Document type: Journal article
Source: BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS; v. 37, n. 1, p. 29-pg., 2023-03-01.
Abstract

We develop here a multivariate generalization of Birnbaum- Saunders (BS) distribution based on the multivariate skew-normal distribu-tion. Some distributional characteristics and properties are presented, as well as a simple and efficient EM algorithm for the iterative computation of the maximum likelihood (ML) estimates of model parameters, through the hi-erarchical representation of the proposed model. The standard errors of the maximum likelihood estimates are calculated from the observed Fisher infor-mation matrix. Moreover, by using the tools, we present a log-linear regres-sion model, where the the ML estimates are once again obtained using an EM algorithm. Finally, simulation studies and two applications to real data sets are presented for illustrating the model and the inferential results devel-oped here. (AU)

FAPESP's process: 22/06421-7 - Extensions of the multivariate Birnbaum-Saunders distribution and its associated regression models
Grantee:Filidor Edilfonso Vilca Labra
Support Opportunities: Scholarships abroad - Research
FAPESP's process: 20/16713-0 - Parametric and semi-parametric regression models under the class of scale mixtures of normal distributions
Grantee:Caio Lucidius Naberezny Azevedo
Support Opportunities: Regular Research Grants