Modified moment estimation for the two-parameter Birnbaum--Saunders distribution
Computational Statistics & Data Analysis
Improved statistical inference for the two-parameter Birnbaum-Saunders distribution
Computational Statistics & Data Analysis
On the hazard function of Birnbaum-Saunders distribution and associated inference
Computational Statistics & Data Analysis
An R implementation for generalized Birnbaum-Saunders distributions
Computational Statistics & Data Analysis
Reference analysis for Birnbaum-Saunders distribution
Computational Statistics & Data Analysis
Inference procedures for the Birnbaum-Saunders distribution and its generalizations
Computational Statistics & Data Analysis
The Birnbaum-Saunders autoregressive conditional duration model
Mathematics and Computers in Simulation
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
Shape and change point analyses of the Birnbaum-Saunders-t hazard rate and associated estimation
Computational Statistics & Data Analysis
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The Birnbaum-Saunders distribution, also known as the fatigue-life distribution, is frequently used in reliability studies. We obtain adjustments to the Birnbaum-Saunders profile likelihood function. The modified versions of the likelihood function were obtained for both the shape and scale parameters, i.e., we take the shape parameter to be of interest and the scale parameter to be of nuisance, and then consider the situation in which the interest lies in performing inference on the scale parameter with the shape parameter entering the modeling in nuisance fashion. Modified profile maximum likelihood estimators are obtained by maximizing the corresponding adjusted likelihood functions. We present numerical evidence on the finite sample behavior of the different estimators and associated likelihood ratio tests. The results favor the adjusted estimators and tests we propose. A novel aspect of the profile likelihood adjustments obtained in this paper is that they yield improved point estimators and tests. The two profile likelihood adjustments work well when inference is made on the shape parameter, and one of them displays superior behavior when it comes to performing hypothesis testing inference on the scale parameter. Two empirical applications are briefly presented.