In this research, the Kumaraswamy Inverse Exponential distribution being a generalization of the Inverse Exponential distribution was applied to six real lifetime datasets. The idea is to assess its flexibility and superiority over its sub-models. Some other properties of the Kumaraswamy Inverse Exponential distribution were investigated in minute details. It was demonstrated and confirmed that the Kumaraswamy Inverse Exponential distribution performed better than the competing probability models except for data sets with variances far above the means. The performance was judged based on the log-likelihood and Akaike Information Criteria (AIC) values posed by the distributions
A new family of distributions called Kumaraswamy-generalized power Weibull (Kgpw) distribution is pr...
In this paper, we develop the new extended Kumaraswamy generated (NEKwG) family of distributions. It...
In this paper, we define and study a new lifetime model called the Kumaraswamy Marshall-Olkin log-lo...
A four parameter Kumaraswamy Exponentiated Inverse Rayleigh distribution (KEIR) introduced in this s...
In this research, the Bayesian estimators of both the unknown model parameters, survivor (or reliab...
A five parameter lifetime statistical model is proposed in this research. The model is called the Ku...
In this work, we introduce a novel generalization of the extended exponential distribution with four...
This paper introduces a new extension of the Inverse Exponential distribution using the framework of...
The aim of the study is to obtain the alpha power Kumaraswamy (APK) distribution. Some main statisti...
Many lifetime distribution models have successfully served as population models for risk analysis an...
In a recent note, Huang and Oluyede (2014) proposed a new model called the exponentiated Kumaraswamy...
In a recent note, Huang and Oluyede (2014) proposed a new model called the exponentiated Kumaraswamy...
A new family of distributions known as Transmuted Kumaraswamy Exponentiated Inverse Rayleigh distrib...
In this paper, a new Kumaraswamy generalized family is proposed. The special sub-models of the famil...
This paper introduces a generalization of moment exponential distribution so called Kumaraswamy Mome...
A new family of distributions called Kumaraswamy-generalized power Weibull (Kgpw) distribution is pr...
In this paper, we develop the new extended Kumaraswamy generated (NEKwG) family of distributions. It...
In this paper, we define and study a new lifetime model called the Kumaraswamy Marshall-Olkin log-lo...
A four parameter Kumaraswamy Exponentiated Inverse Rayleigh distribution (KEIR) introduced in this s...
In this research, the Bayesian estimators of both the unknown model parameters, survivor (or reliab...
A five parameter lifetime statistical model is proposed in this research. The model is called the Ku...
In this work, we introduce a novel generalization of the extended exponential distribution with four...
This paper introduces a new extension of the Inverse Exponential distribution using the framework of...
The aim of the study is to obtain the alpha power Kumaraswamy (APK) distribution. Some main statisti...
Many lifetime distribution models have successfully served as population models for risk analysis an...
In a recent note, Huang and Oluyede (2014) proposed a new model called the exponentiated Kumaraswamy...
In a recent note, Huang and Oluyede (2014) proposed a new model called the exponentiated Kumaraswamy...
A new family of distributions known as Transmuted Kumaraswamy Exponentiated Inverse Rayleigh distrib...
In this paper, a new Kumaraswamy generalized family is proposed. The special sub-models of the famil...
This paper introduces a generalization of moment exponential distribution so called Kumaraswamy Mome...
A new family of distributions called Kumaraswamy-generalized power Weibull (Kgpw) distribution is pr...
In this paper, we develop the new extended Kumaraswamy generated (NEKwG) family of distributions. It...
In this paper, we define and study a new lifetime model called the Kumaraswamy Marshall-Olkin log-lo...