Reparameterized birnbaum-saunders regression models with varying precision

Manoel Santos-Neto, Francisco José A. Cysneiros, Víctor Leiva, Michelli Barros

Research output: Contribution to journalArticlepeer-review

51 Scopus citations


We propose a methodology based on a reparameterized Birnbaum-Saunders regression model with varying precision, which generalizes the existing works in the literature on the topic. This methodology includes the estimation of model parameters, hypothesis tests for the precision parameter, a residual analysis and influence diagnostic tools. Simulation studies are conducted to evaluate its performance. We apply it to two real-world case-studies to show its potential with the R software.

Original languageEnglish
Pages (from-to)2825-2855
Number of pages31
JournalElectronic Journal of Statistics
Issue number2
StatePublished - 1 Jan 2016
Externally publishedYes


  • Birnbaum-saunders distribution
  • Hypothesis testing
  • Likelihood-based methods
  • Local influence
  • Monte carlo simulation
  • R software
  • Residuals


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