Two New Mixture Models Related to the Inverse Gaussian Distribution

Samuel Kotz (), Víctor Leiva () and Antonio Sanhueza ()
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Samuel Kotz: The George Washington University
Víctor Leiva: Universidad de Valparaíso
Antonio Sanhueza: Universidad de La Frontera

Methodology and Computing in Applied Probability, 2010, vol. 12, issue 1, 199-212

Abstract: 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.

Keywords: Birnbaum-Saunders distribution; Goodness-of-fit; Likelihood methods; Moments; Sinh-normal distribution; Primary 60E05; Secondary 62N05 (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s11009-008-9112-4

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