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Generalized Truncated Fréchet Generated Family Distributions and Their Applications

Computer Modeling in Engineering & Sciences 2021年第2期126卷 791-819页

作者： Ramadan A.ZeinEldin Christophe Chesneau Farrukh Jamal Mohammed Elgarhy Abdullah M.Almarashi Sanaa Al-Marzouki Deanship of Scientific Research King AbdulAziz UniversityJeddah21589Saudi Arabia Faculty of Graduate Studies for Statistical Research Cairo UniversityAl OrmanGiza Governorate12613Egypt Universite de Caen LMNOCampus IIScience 3Caen14032France Department of Statistics The Islamia University of BahawalpurPunjab63100Pakistan The Higher Institute of Commercial Sciences Al Mahalla Al KubraAlgarbia31951Egypt Statistics Department Faculty of ScienceKing AbdulAziz UniversityJeddah21551Saudi Arabia

Understanding a phenomenon from observed data requires contextual and efficient statistical *** models are based on probability distributions having sufficiently flexible statistical properties to adapt to a maximum of *** examples include the distributions of the truncated Fréchet generated *** this paper,we go even further by introducing a more general family,based on a truncated version of the generalized Fréchet *** generalization involves a new shape parameter modulating to the extreme some central and dispersion parameters,as well as the skewness and weight of the *** also investigate the main functions of the new family,stress-strength parameter,diverse functional series expansions,incomplete moments,various entropy measures,theoretical and practical parameters estimation,bivariate extensions through the use of copulas,and the estimation of the model *** considering a special member of the family having the Weibull distribution as the parent,we fit two data sets of interest,one about waiting times and the other about *** statistical criteria attest that the proposed model is superior over other extended Weibull models,including the one derived to the former truncated Fréchet generated family.

关键词： Truncated distribution general family of distributions incomplete moments entropy copula data analysis

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