期刊名称：Pakistan Journal of Statistics and Operation Research
印刷版ISSN：2220-5810
出版年度：2020
卷号：16
期号：2
页码：373-386
DOI：10.18187/pjsor.v16i2.3298
语种：English
出版社：College of Statistical and Actuarial Sciences
摘要：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.
关键词：Reciprocal Exponential Distribution;Morgenstern Family Moments;Clayton Copula;Estimation;Simulations;Odd Log-Logistic Family
