On the DUS-Kumaraswamy Distribution

Abstract

Kumaraswamy distribution is introduced by [7] and it is particularly useful for many natural phenomena whose outcomes have lower and upper bounds or bounded outcomes in biomedical and epidemiological research (see [12]). In this paper, a new statistical distribution called DUS-Kumaraswamy is introduced by using DUS transformation (which is recently introduced by [6]) on Kumaraswamy distribution. The proposed distribution has the same domain as Kumaraswamy and it can be used as an alternative model to describe the natural phenomena mentioned above. Several distributional properties such as mean, variance, skewness, kurtosis, Lorenz and Bonferroni curves are studied. The statistical inference on the parameters of Dus-Kumaraswamy is discussed by maximum likelihood methodology. A simulation study is conducted to observe the behaviors of maximum likelihood estimates under different conditions. A numerical example is also presented.

Keywords

• Data analysis
• Kumaraswamy distribution
• Maximum likelihood estimator
• Monte Carlo simulation

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