The linear exponential distribution is a very well-known distribution for modeling lifetime data in reliability and medical studies. We introduce in this paper a new four-parameter generalized version of the linear exponential distribution which is called Kumaraswamy linear exponential distribution. We provide a comprehensive account Kumaraswamy (log-EK) distribution, which extends the generalized exponential (Gupta and Kundu, 1999) and double generalized exponential (Barreto-Souza et al., 2010) distributions, and provide some mathematical properties. A new continuous distribution called exponentiated Kumaraswamy-exponential that extends the exponential distribution and some other distributions is proposed and studied. Several structural properties of the new distribution were investigated, including the moments, hazard function, mean deviations and Rényi entropy. Moreover, we discuss the maximum likelihood estimation of this distribution. Based on the Kumaraswamy distribution, we study the so called Kumaraswamy Extension Exponential Distribution (KEE). The new distribution has a number of well-known lifetime special sub-models such as a new exponential type distribution, extension exponential distribution Kumaraswamy generalized exponential distribution, among several others. The Kumaraswamy Exponential{Weibull Distribution: Theory and Applications Gauss M. Cordeiro y, Abdus Saboor , Muhammad Nauman Khanz, Gamze Ozelxand Marcelino A.R. Pascoa{Abstract Signi cant progress has been made towards the generalization of some well{known lifetime models, which have been successfully applied to power Weibull, Kumaraswamy generalized power exponential distributions. Some statistical properties of the new distribution include its moments, moment generating function, quantile function and hazard function are In this article, the five-parameter beta Kumaraswamy exponential distribution (BKw-E) is introduced, and some characterizations of this distribution are obtained. The shape of the hazard function In this article, the five-parameter beta Kumaraswamy exponential distribution (BKw-E) is introduced, and some characterizations of this distribution are obtained. The shape of the hazard function and some other important properties—such as median, mode, quantile function, and mean—are studied. In addition, the moments, skewness, and kurtosis are found. In this paper, we introduce a veparameter distribution obtained by applying the Kumaraswamy generator dened by Cordeiro et al. [6] to the exponential-Weibull model given by Cordeiro et al. [5]. Interestingly, the proposed model has increasing, upside-down bathtub and bathtub shaped hazard rate functions. By means of a real lifetime data set, we prove that the new distribution provides a better fit than the Kumaraswamy Weibull, Marshall-Olkin exponential-Weibull, extended Weibull, exponential
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