A Generalization of Reciprocal Exponential Model: Clayton Copula, Statistical Properties and Modeling Skewed and Symmetric Real Data Sets
Mahmoud M. Mansour, Nadeem Shafique Butt, Haitham M. Yousof, Saiful Islam Ansari, Mohamed Ibrahim
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.
Topics & Concepts
MathematicsCopula (linguistics)ReciprocalExponential familyBivariate analysisEstimatorExponential functionStatisticsUnivariateApplied mathematicsEconometricsGeneralizationExponential distributionMultivariate statisticsMathematical analysisPhilosophyLinguisticsStatistical Distribution Estimation and ApplicationsFinancial Risk and Volatility ModelingProbabilistic and Robust Engineering Design