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Research Article Open access CC BY 4.0

Generalized Rank Mapped Transmuted Distributions with Properties and Application: A Review

. Imliyangba, Bhanita Das, Seema Chettri

Asian Journal of Probability and Statistics · pp. 44–61 · Published 10 Jun 2021

10.9734/ajpas/2021/v13i330309

Abstract

Generalizing probability distributions is a very common practice in the theory of statistics. Researchers have proposed several generalized classes of distributions which are very flexible and convenient to study various statistical properties of the distribution and its ability to fit the real-life data. Several methods are available in the literature to generalize new family of distributions. The Quadratic Rank Transmutation Map (QRTM) is a tool for the construction of new families of non-Gaussian distributions and to modulate a given base distribution for modifying the moments like the skewness and kurtosis with the ability to explore its tail properties and improve the adequacy of the distribution. Recently, a new family of transmutation map, defined as Cubic Rank Transmutation (CRT) has been used by several authors to develop new distributions with application to real-life data. In this article, we have done a review work on the existing generalized rank mapped transmuted probability distributions, available in the literature with various statistical properties such as the reliability, hazard rate and cumulative hazard functions, moments, mean, variance, moment-generating function, order statistics, generalized entropy and quantile function along with its applications. Some future works have also been discussed for generalized rank mapped transmuted distributions.

Transmutation Generalized Rank Probability Distribution Quadratic Transmutation Cubic Rank Transmutation Quartic Rank Transmutation

Cited by 2

Comparative Analysis and Practical Applications of Cubic Transmutations for the Pareto Distribution

Edoh Katchekpele, Issa Cherif Geraldo, Tchilabalo Abozou Kpanzou · International Journal of Mathematics and Mathematical Sciences · 2025

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