However, in recent years, applications from the environmental, financial, biomedical sciences, engineering among others, have further shown that data sets following the classical distributions are more often the exception rather than the reality. In fact, the statistics literature is filled with hundreds of continuous univariate distributions. Because of this, considerable effort has been expended in the development of large classes of standard probability distributions along with revelent statistical methodologies. The quality of the procedures used in a statistical analysis depends heavily on the assumed probability model or distributions.
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