ABSTRACTThe log-Birnbaum-Saunders regression model introduced by Rieck and Nedelman (1991) is useful for modeling lifetimes of materials and equipments subject to different conditions. Our goal in this article is twofold. First, we numerically evaluate the finite sample performances of the likelihood ratio, score and Wald tests in the log-Birnbaum-Saunders regression model. Second, we introduce a RESET-like misspecification test for that model. The null hypothesis is that the model is correctly specified which is tested against the alternative hypothesis of model misspecification. The power of the test is evaluated using Monte Carlo simulations. Bootstrap-based inference is also considered. An empirical application is presented and discussed.
['Jéssica de Lima Santos', 'Francisco Cribari-Neto']
Hypothesis Testing in Log-Birnbaum-Saunders Regressions