Ramadan A. ZeinEldin1,2, Christophe Chesneau3,*, Farrukh Jamal4, Mohammed Elgarhy5, Abdullah M. Almarashi6, Sanaa Al-Marzouki6
CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.2, pp. 791-819, 2021, DOI:10.32604/cmes.2021.012169
Abstract Understanding a phenomenon from observed data requires contextual and efficient statistical models. Such models
are based on probability distributions having sufficiently flexible statistical properties to adapt to a maximum of
situations. Modern examples include the distributions of the truncated Fréchet generated family. In this paper,
we go even further by introducing a more general family, based on a truncated version of the generalized Fréchet
distribution. This generalization involves a new shape parameter modulating to the extreme some central and
dispersion parameters, as well as the skewness and weight of the tails. We also investigate the main functions of the
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