An R implementation for generalized Birnbaum-Saunders distributions

Michelli Barros, Gilberto A. Paula, Víctor Leiva

Research output: Contribution to journalArticlepeer-review

50 Scopus citations

Abstract

The Birnbaum-Saunders (BS) model is a positively skewed statistical distribution that has received great attention in recent decades. A generalized version of this model was derived based on symmetrical distributions in the real line named the generalized BS (GBS) distribution. The R package named gbs was developed to analyze data from GBS models. This package contains probabilistic and reliability indicators and random number generators from GBS distributions. Parameter estimates for censored and uncensored data can also be obtained by means of likelihood methods from the gbs package. Goodness-of-fit and diagnostic methods were also implemented in this package in order to check the suitability of the GBS models. In this article, the capabilities and features of the gbs package are illustrated by using simulated and real data sets. Shape and reliability analyses for GBS models are presented. A simulation study for evaluating the quality and sensitivity of the estimation method developed in the package is provided and discussed.

Original languageEnglish
Pages (from-to)1511-1528
Number of pages18
JournalComputational Statistics and Data Analysis
Volume53
Issue number4
DOIs
StatePublished - 15 Feb 2009
Externally publishedYes

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