A new skew generalization of the normal distribution: Properties and applications
Computational Statistics & Data Analysis
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The use of the Marshall-Olkin transformation as a skewing mechanism is investigated. The distributions obtained when this transformation is applied to several classes of symmetric and unimodal distributions are analysed. It is shown that most of the resulting distributions are not flexible enough to model data presenting high or moderate skewness. The only case encountered where the Marshall-Olkin transformation can be considered a useful skewing mechanism is when applied to Student-t distributions with Cauchy or even heavier tails.