Mixture Model on Development of Bivariate Product Distribution and its Properties

Udochukwu Victor Echebiri *

Department of Statistics, Faculty of Physical Sciences, University of Benin, Benin, Nigeria.

Akpome Jennifer Nomuoja

Department of Statistics, Faculty of Sciences, Dennis Osadebay University, Asaba, Delta State, Nigeria.

Chimezie Stanley Ngene

Digital Banking Department, Polaris Bank Limited, Lagos State, Nigeria.

Emwinloghosa Kenneth Guobadia

Department of Administration, Federal Medical Centre, Asaba, Delta State, Nigeria.

Jophet Ewere Okoh

Department of Statistics, Faculty of Sciences, Dennis Osadebay University, Asaba, Delta State, Nigeria.

*Author to whom correspondence should be addressed.


Abstract

In the study, some bivariate distributions were developed from mixture model offspring, using the Independent (Product) distribution approach. These developments are categorized under the IID and IInD: where the Bivariate Exponential distribution, Bivariate Lindley distribution and Bivariate Juchez distribution are constructed as IIDs; and Bivariate Exponential-Lindley distribution, Bivariate Exponential-Juchez distribution and Bivariate Lindley-Juchez distribution as (IInDs). The properties of these distributions which involve: the shape of the bivariate PDFs, moments, moment generating function, mean, covariance and coefficient of correlation, maximum likelihood estimator, reliability analysis, renewal property and probability patterns; are studied across the distributions. Finally, under renewal properties, functions are derived which can model two-dimensional queuing and renewal processes, for events where the arrival and service times are dependent.     

Keywords: Mixture model, bivariate derivations, product distribution, renewal property


How to Cite

Echebiri, Udochukwu Victor, Akpome Jennifer Nomuoja, Chimezie Stanley Ngene, Emwinloghosa Kenneth Guobadia, and Jophet Ewere Okoh. 2022. “Mixture Model on Development of Bivariate Product Distribution and Its Properties”. Asian Journal of Probability and Statistics 20 (4):100-119. https://doi.org/10.9734/ajpas/2022/v20i4443.

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