Influence diagnostics in log-Birnbaum-Saunders regression models with censored data

Víctor Leiva, Michelli Barros, Gilberto A. Paula, Manuel Galea

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104 Scopus citations


In this paper we discuss log-Birnbaum-Saunders regression models with censored observations. This kind of model has been largely applied to study material lifetime subject to failure or stress. The score functions and observed Fisher information matrix are given as well as the process for estimating the regression coefficients and shape parameter is discussed. The normal curvatures of local influence are derived under various perturbation schemes and two deviance-type residuals are proposed to assess departures from the log-Birnbaum-Saunders error assumption as well as to detect outlying observations. Finally, a data set from the medical area is analyzed under log-Birnbaum-Saunders regression models. A diagnostic analysis is performed in order to select an appropriate model.

Original languageEnglish
Pages (from-to)5694-5707
Number of pages14
JournalComputational Statistics and Data Analysis
Issue number12
StatePublished - 15 Aug 2007
Externally publishedYes


  • Birnbaum-Saunders distribution
  • Generalized leverage
  • Influence diagnostic
  • Lifetime distributions
  • Local influence
  • Log-linear model
  • Maximum likelihood estimator
  • Residual analysis
  • Sinh-normal distribution


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