On a new class of skewed Birnbaum-Saunders models

Scale mixtures of Birnbaum–Saunders (SBS) distributions are attractive models in lifetime analysis. These models are based on scale mixture of normal (SMN) distributions and provide flexible heavy-tailed distributions. In this article, we propose a skewed version of SBS distributions and we establish some of its probabilistic and inferential properties. We then discuss the maximum likelihood estimation of the model parameters. An illustration of the methodology is provided, using real data.

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