Two new mixture models related to the inverse Gaussian distribution

Samuel Kotz, VICTOR ELISEO LEIVA SANCHEZ, Antonio Sanhueza

Research output: Contribution to journalArticlepeer-review

33 Scopus citations

Abstract

This article presents a new family of logarithmic distributions to be called the sinh mixture inverse Gaussian model and its associated life distribution referred as the extended mixture inverse Gaussian model. Specifically, the density, distribution function, and moments are developed for the sinh mixture inverse Gaussian distribution. Next, the extended mixture inverse Gaussian distribution is characterized. A graphical analysis of the densities of the new models is also provided. In addition, a lifetime analysis is presented for the extended mixture inverse Gaussian distribution. Finally, an example with a real data set is given to illustrate the methodology, which indicates that the new models result in a better fit to the data than some other well-known distributions.

Original languageEnglish
Pages (from-to)199-212
Number of pages14
JournalMethodology and Computing in Applied Probability
Volume12
Issue number1
DOIs
StatePublished - 1 Mar 2010

Keywords

  • Birnbaum-Saunders distribution
  • Goodness-of-fit
  • Likelihood methods
  • Moments
  • Sinh-normal distribution

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