Statistical Modelling 14 (1) (2014), 2148
Birnbaum–Saunders statistical modelling: a new approach
Víctor Leiva
Departamento de Estadística,
Universidad de Valparaíso,
Chile
e-mail: victor.leiva@uv.cl
Manoel Santos-Neto
Departamento de Estatística,
Universidade Federal de Campina Grande,
Brazil
Francisco José A Cysneiros
Departamento de Estatística,
Universidade Federal de Pernambuco,
Brazil
Michelli Barros
Departamento de Estatística,
Universidade Federal de Campina Grande,
Brazil
Abstract:
Modelling based on the Birnbaum–Saunders distribution has received considerable attention in recent years. In this article, we introduce a new approach for Birnbaum–Saunders regression models, which allows us to analyze data in their original scale and to model non-constant variance. In addition, we propose four types of residuals for these models and conduct a simulation study to establish which of them has a better performance. Moreover, we develop methods of local influence by calculating the normal curvatures under different perturbation schemes. Finally, we perform a statistical analysis with real data by using the approach proposed in the article. This analysis shows the potentiality of our proposal.
Keywords:
Birnbaum–Saunders; distribution; data analysis; influence diagnostics; Monte Carlo methods; reparameterization residuals
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