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Estimation of Kumaraswamy Distribution Parameters Using the Principle of Maximum Entropy |
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PP: 131-144 |
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doi:10.18576/jsap/130109
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Author(s) |
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M. R. Mahmoud,
A. M. Saad,
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Abstract |
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| This paper proposes using maximum entropy approach to estimate the parameters of the Kumaraswamy distribution subject to moment constraints. Kumaraswamy [7] introduced the double pounded probability density function which was originally used to model hydrological phenomena. It was mentioned that this probability density function is applicable to bounded natural phenomena which have values on two sides. The distribution share several properties with the beta distribution and it has the extra advantages that is possesses a closed form distribution function, but it remained unknown to most statisticians until it was developed by Jones [6] as a beta-type distribution with some tractability advantages in particular as it has fairly simple quantile function and it has explicit formula for L-Moment. Using the principle of maximum entropy to propose new estimators for the Kumaraswamy parameters and compared with maximum likelihood and Bayesian estimation methods. A simulation study is performed to investigate the performance of the estimators in terms of their mean square errors and their efficiency.
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