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Department of Mathematical Sciences Faculty Publications

Series

2015

Generalized Distribution

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Estimation In The Exponentiated Kumaraswamy Dagum Distribution With Censored Samples, Broderick O. Oluyede, Shujiao Huang Apr 2015

Estimation In The Exponentiated Kumaraswamy Dagum Distribution With Censored Samples, Broderick O. Oluyede, Shujiao Huang

Department of Mathematical Sciences Faculty Publications

In a recent note, Huang and Oluyede (2014) proposed a new model called the exponentiated Kumaraswamy Dagum (EKD) distribution with applications to income and lifetime data. In this note, this distribution is shown to be a very competitive model for describing censored observations in lifetime reliability problems. This work shows that in certain cases, the EKD distribution performs better than other parametric model such as the exponentiated Kumaraswamy Weibull distribution and its sub-models, which include some of the commonly used models in survival analysis and reliability analysis, such as the exponentiated Weibull, Weibull and exponential distributions.


A Generalized Class Of Kumaraswamy Lindley Distribution With Applications To Lifetime Data, Broderick O. Oluyede, Tiantian Yang, Bernard Omolo Jan 2015

A Generalized Class Of Kumaraswamy Lindley Distribution With Applications To Lifetime Data, Broderick O. Oluyede, Tiantian Yang, Bernard Omolo

Department of Mathematical Sciences Faculty Publications

In this paper, we propose a new class of generalized distributions called the Exponentiated Kumaraswamy Lindley (EKL) distribution, as well as related sub-distributions. This class of distributions contains the Kumaraswamy Lindley (KL), generalized Lindley (GL), and Lindley (L) distributions as special cases. A series expansion of the density is obtained. Statistical properties of this class of distributions, including the hazard and reverse hazard functions, monotonicity property, shapes, moments, reliability, quantile function, mean deviations, Bonferroni and Lorenz curves, entropy and Fisher information are derived among others. The method of maximum likelihood is adopted for estimating the model parameters. Two applications to …