Abstract
The generalization of probability distributions in view of improving their flexibility in capturing the shape and tail behavior of disparate data sets has become one of the most active aspects of statistical research. We developed a new Pareto distribution by using Kumaraswamy method which gave rise to a new distribution called Kumaraswamy Pareto distribution. This method is called transmutation. The mathematical properties of the new generalized distribution was presented using quartiles, moments, entropy, order statistics mean deviation and maximum likelihood method of parameter estimation. The new generalized distribution was applied to a real life data on the exceedances of flood peaks (in m3/s) where it was observed to be superior to its sub models in terms of some goodness-of-fit test such as log likelihood criterion, Akaike Information Criterion (AIC) and Kolmogorov-Smirnov (K-S) measures.
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