Random number generators for the generalized Birnbaum-Saunders distribution

Víctor Leiva, Antonio Sanhueza, Pranab K. Sen, Gilberto A. Paula

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

The generalized Birnbaum-Saunders distribution pertains to a class of lifetime models including both lighter and heavier tailed distributions. This model adapts well to lifetime data, even when outliers exist, and has other good theoretical properties and application perspectives. However, statistical inference tools may not exist in closed form for this model. Hence, simulation and numerical studies are needed, which require a random number generator. Three different ways to generate observations from this model are considered here. These generators are compared by utilizing a goodness-of-fit procedure as well as their effectiveness in predicting the true parameter values by using Monte Carlo simulations. This goodness-of-fit procedure may also be used as an estimation method. The quality of this estimation method is studied here. Finally, through a real data set, the generalized and classical Birnbaum-Saunders models are compared by using this estimation method.

Original languageEnglish
Pages (from-to)1105-1118
Number of pages14
JournalJournal of Statistical Computation and Simulation
Volume78
Issue number11
DOIs
StatePublished - 2008
Externally publishedYes

Keywords

  • Elliptical distributions
  • Goodness-of-fit
  • Inverse Gaussian distribution
  • Monte Carlo simulation
  • Sinh-normal distribution

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