Date of Award

8-2015

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mathematics

First Advisor

Mavis Pararai, Ph.D.

Second Advisor

Christoph E. Maier, Ph.D.

Third Advisor

Russell Stocker, Ph.D.

Abstract

The aim of this thesis is to propose a new distribution called the Kumaraswamy inverse Weibull Poisson (KIWP) Distribution. The distribution properties including hazard functions, reverse hazard functions, survival functions, quantile functions, moments, distributions of order statistics, mean deviations, Lorenz and Bonferroni curves and Fischer information are presented. The maximum likelihood method is used to estimate the model parameters of this new distribution. The special cases of the KIWP distribution including the inverse Weibull Poisson (IWP), Kumaraswamy Frechet Poisson (KFP), Kumaraswamy inverse exponentiated Poisson (KIEP) and Kumaraswamy inverse Rayleigh Poisson (KIRP) distributions are presented. A Monte Carlo simulation study is presented to exhibit the performance and accuracy of the maximum likelihood estimates of the KIWP model parameters. Real data examples are used to show the usefulness of the proposed model.

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