Slashed lomax distribution and regression model

Abstract

In this article, the slashed Lomax distribution is introduced, which is an asymmetric distribution and can be used for fitting thick-tailed datasets. Various properties are explored, such as the density function, hazard rate function, Renyi entropy, r-th moments, and the coefficients of the skewness and kurtosis. Some useful characterizations of this distribution are obtained. Furthermore, we study a slashed Lomax regression model and the expectation conditional maximization (ECM) algorithm to estimate the model parameters. Simulation studies are conducted to evaluate the performances of the proposed method. Finally, two sets of data are applied to verify the importance of the slashed Lomax distribution. The Lomax distribution, which was introduced by Lomax [1], has been regarded as the mixed distribution of the exponential distribution and gamma distribution. It has a heavy-tailed probability distribution, often used in business, economics, and actuarial modeling. Let X be a non-negative random variable with a Lomax distribution, then its probability density function (pdf) is given by,