Birnbaum-Saunders statistical modelling: A new approach

VICTOR ELISEO LEIVA SANCHEZ, Manoel Santos-Neto, Francisco José A Cysneiros, Michelli Barros

Research output: Contribution to journalArticlepeer-review

52 Scopus citations

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.

Original languageEnglish
Pages (from-to)21-48
Number of pages28
JournalStatistical Modelling
Volume14
Issue number1
DOIs
StatePublished - 1 Feb 2014

Keywords

  • Birnbaum-Saunders distribution
  • data analysis
  • influence diagnostics
  • Monte Carlo methods
  • reparameterization
  • residuals

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