A new family of distributions called exponentiated Kumaraswamy-Dagum (EKD) distribution is proposed and studied. This family includes several well known sub-models, such as Dagum (D), Burr III (BIII), Fisk or Log-logistic (F or LLog), and new sub-models, namely, Kumaraswamy-Dagum (KD), Kumaraswamy-Burr III (KBIII), Kumaraswamy-Fisk or Kumaraswamy-Log-logistic (KF or KLLog), exponentiated Kumara...

Many lifetime distribution models have successfully served as population models for risk analysis and reliability mechanisms. The Kumaraswamy distribution is one of these distributions which is particularly useful to many natural phenomena whose outcomes have lower and upper bounds or bounded outcomes in the biomedical and epidemiological research. This paper studies point estimation and interv...

In this article, we propose a generalization of the modified inverse Weibull distribution. The generalization are motivated by the recent work of Cordeiro et al. [2] and are based on the Kumaraswamy distribution. The generalized distribution is called the Kumaraswamy modified inverse Weibull(KMIW) distribution. We provide a comprehensive description of the structural properties of the subject d...

In this paper, the Kumaraswamy-geometric distribution, which is a member of the T -geometric family of discrete distributions is defined and studied. Some properties of the distribution such as moments, probability generating function, hazard and quantile functions are studied. The method of maximum likelihood estimation is proposed for estimating the model parameters. Two real data sets are us...

in this paper, we propose and study exp-kumaraswamy distribution. some of its properties  are derived, including the density function, hazard rate function, quantile function, moments,  skewness  and kurtosis.   adata set isused to illustrate an application of the proposed distribution. also, we obtain a new distribution by transformation onexp-kumaraswamy distribution.   new distribution is an...

The Kumaraswamy distribution is similar to the Beta distribution but has the key advantage of a closed-form cumulative distribution function. In this paper we present the estimation of Kumaraswamy distribution parameters based on Generalized Order Statistics (GOS) using Maximum Likelihood Estimators (MLE). We proved that the parameters estimation for Kumaraswamy distribution can not be obtained...

In this paper, we propose and study exp-kumaraswamy distribution. Some of its properties  are derived, including the density function, hazard rate function, quantile function, moments,  skewness  and kurtosis.   Adata set isused to illustrate an application of the proposed distribution. Also, we obtain a new distribution by transformation onexp-kumaraswamy distribution.   New distribution is an...