Diagnostics in Birnbaum-Saunders accelerated life models with an application to fatigue data

Víctor Leiva, Edgardo Rojas, Manuel Galea, Antonio Sanhueza

Research output: Contribution to journalArticlepeer-review

48 Scopus citations


In industrial statistics, there is great interest in predicting with precision lifetimes of specimens that operate under stress. For example, a bad estimation of the lower percentiles of a life distribution can produce significant monetary losses to organizations due to an excessive amount of warranty claims. The Birnbaum-Saunders distribution is useful for modeling lifetime data. This is because such a distribution allows us to relate the total time until the failure occurs to some type of cumulative damage produced by stress. In this paper, we propose a methodology for detecting influence of atypical data in accelerated life models on the basis of the Birnbaum-Saunders distribution. The methodology developed in this study should be considered in the design of structures and in the prediction of warranty claims. We conclude this work with an application of the proposed methodology on the basis of real fatigue life data, which illustrates its importance in a warranty claim problem.

Original languageEnglish
Pages (from-to)115-131
Number of pages17
JournalApplied Stochastic Models in Business and Industry
Issue number2
StatePublished - 2014
Externally publishedYes


  • exponential and power law accelerated life models
  • industrial statistics
  • life distributions
  • local influence


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