Estimation of extreme percentiles in BirnbaumSaunders distributions

Filidor Vilca, Lucia Santana, Víctor Leiva, N. Balakrishnan

Research output: Contribution to journalArticlepeer-review

45 Scopus citations

Abstract

The BirnbaumSaunders distribution has recently received considerable attention in the statistical literature, including some applications in the environmental sciences. Several authors have generalized this distribution, but these generalizations are still inadequate for predicting extreme percentiles. In this paper, we consider a variation of the BirnbaumSaunders distribution, which enables the prediction of extreme percentiles as well as the implementation of the EM algorithm for maximum likelihood estimation of the distribution parameters. This implementation has some advantages over the direct maximization of the likelihood function. Finally, we present results of a simulation study along with an application to a real environmental data set.

Original languageEnglish
Pages (from-to)1665-1678
Number of pages14
JournalComputational Statistics and Data Analysis
Volume55
Issue number4
DOIs
StatePublished - 1 Apr 2011
Externally publishedYes

Keywords

  • EM and ECM algorithms
  • Monte Carlo simulations
  • Skew distributions

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