A log Birnbaum-Saunders regression model based on the skew-normal distribution under the centred parameterization

In this paper, we introduce a new regression model for positive and skewed data, a log Birnbaum-Saunders model based on the centred skew-normal distribution, and we present a several inference tools for this model. Initially, we developed a new version of skew-sinh-normal distribution and we describe some of its properties. For the proposed regression model, we carry out, through of the expectation conditional maximization (ECM) algorithm, the parameter estimation, model fit assessment, model comparison and residual analysis. Finally, our model accommodates more suitably the asymmetry of the data, compared with the usual log Birnbaum-Saunders model, which is illustrated through real data analysis.