Innovative approaches for modifying probability distributions

This study details innovative techniques for modifying standard probability distributions to better accommodate non-symmetrical real-world data and identify an appropriate fit for such skewed datasets. Several well-established methods are available for these transformations, including the Marshall-Olkin method, Harris method, weighted distribution method, mixed-type distribution method, and the Decreasing Uniform Scale (DUS) transformation method. Furthermore, the effects of these methods are distinguished, and suitable methodologies for identifying the best fit, such as graphical analysis, information criteria, and statistical tests, are explained.