Marshall-olkin extended inverted kumaraswamy distribution for modeling of wind speed data

Abstract

Many important factors need to be taken into account when assessing the wind energy potential of a place. These include precisely determining the distribution to be used for the analysis of wind speed data and precisely estimating the model parameters. The current study has two main goals: the first is to estimate the parameters of the Marshall Olkin extended inverted Kumaraswamy (MOEIK) distribution, and the second is to use it to model wind speed data. For parameter estimation, four renowned estimation methods are used: maximum likelihood, Anderson Darling, Cramer von Misses, and ordinary least squares. A comprehensive simulation study is used to evaluate the behavior of these derived estimators, and maximum likelihood is found to efficiently estimate the parameters. For this study, wind speed data was collected from three stations in Sanghar, Tandoghulamali, and Umerkot. The results indicated that the MOIKw distribution provides efficient fitting based on the goodness-of-fit measures among competitive distributions.