Elliptically contoured models in statistics
Elliptically contoured models in statistics
Assessment of local influence in elliptical linear models with longitudinal structure
Computational Statistics & Data Analysis
Improved statistical inference for the two-parameter Birnbaum-Saunders distribution
Computational Statistics & Data Analysis
Diagnostics analysis for log-Birnbaum-Saunders regression models
Computational Statistics & Data Analysis
Influence diagnostics in log-Birnbaum-Saunders regression models with censored data
Computational Statistics & Data Analysis
A new family of life distributions for dependent data: Estimation
Computational Statistics & Data Analysis
Lifetime analysis based on the generalized Birnbaum-Saunders distribution
Computational Statistics & Data Analysis
On the hazard function of Birnbaum-Saunders distribution and associated inference
Computational Statistics & Data Analysis
On Birnbaum-Saunders inference
Computational Statistics & Data Analysis
Testing hypotheses in the Birnbaum-Saunders distribution under type-II censored samples
Computational Statistics & Data Analysis
Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance
Applied Stochastic Models in Business and Industry
Diagnostics for a class of survival regression models with heavy-tailed errors
Computational Statistics & Data Analysis
Shape and change point analyses of the Birnbaum-Saunders-t hazard rate and associated estimation
Computational Statistics & Data Analysis
Generalized Birnbaum-Saunders kernel density estimators and an analysis of financial data
Computational Statistics & Data Analysis
Lower confidence limit for reliability based on grouped data using a quantile-filling algorithm
Computational Statistics & Data Analysis
| Hi-index | 0.03 |
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.