A Generalization of Reciprocal Exponential Model: Clayton Copula, Statistical Properties and Modeling Skewed and Symmetric Real Data Sets | [Pakistan Journal of Statistics and Operation Research • 2020]

Author(s):

1. M. M. Mansour: Department of MIS, Yanbu, Taibah University, Saudi Arabia; Department of Statistics, Mathematics and Insurance, Benha University, Egypt

2. Nadeem Shafique Butt: Department of Family and Community Medicine, King Abdul Aziz University, Jeddah, Kingdom of, Saudi Arabia

3. Haitham M. Yousof: Department of Statistics, Mathematics and Insurance, Benha University, Egypt

4. S. I. Ansari: Department of Business Administration, Azad institute of Engineering and Technology, Lucknow, India

5. Mohamed Ibrahim: Department of Applied Statistics and Insurance, Faculty of Commerce, Damietta University, Damietta, Egypt

Abstract:

We introduce a new extension of the reciprocal Exponential distribution for modeling the extreme values. We used the Morgenstern family and the clayton copula for deriving many bivariate and multivariate extensions of the new model. Some of its properties are derived. We assessed the performance of the maximum likelihood estimators (MLEs) via a graphical simulation study. The assessment was based on the sample size. The new reciprocal model is employed for modeling the skewed and the symmetric real data sets. The new reciprocal model is better than some other important competitive models in statistical modeling.

Page(s): 373-386

DOI: 10.18187/pjsor.v16i2.3298

Published: Journal: Pakistan Journal of Statistics and Operation Research, Volume: 16, Issue: 2, Year: 2020

Keywords:

simulations , Estimation , Clayton Copula , Morgenstern Family Moments , Reciprocal Exponential Distribution , Odd LogLogistic Family

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