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Type II Power Topp-Leone Generated Family of Distributions with Statistical Inference and Applications

Rashad A. R. Bantan, Farrukh Jamal, Christophe Chesneau, Mohammed Elgarhy

2020Symmetry52 citationsDOIOpen Access PDF

Abstract

In this paper, we present and study a new family of continuous distributions, called the type II power Topp-Leone-G family. It provides a natural extension of the so-called type II Topp-Leone-G family, thanks to the use of an additional shape parameter. We determine the main properties of the new family, showing how they depend on the involving parameters. The following points are investigated: shapes and asymptotes of some important functions, quantile function, some mixture representations, moments and derivations, stochastic ordering, reliability and order statistics. Then, a special model of the family based on the inverse exponential distribution is introduced. It is of particular interest because the related probability functions are tractable and possess various kinds of asymmetric shapes. Specially, reverse J, left skewed, near symmetrical and right skewed shapes are observed for the corresponding probability density function. The estimation of the model parameters is performed by the use of three different methods. A complete simulation study is proposed to illustrate their numerical efficiency. The considered model is also applied to analyze two different kinds of data sets. We show that it outperforms other well-known models defined with the same baseline distribution, proving its high level of adaptability in the context of data analysis.

Topics & Concepts

MathematicsExponential familyQuantile functionNatural exponential familyProbability density functionApplied mathematicsInferenceQuantileType (biology)Context (archaeology)AsymptoteProbability distributionOrder statisticStatisticsMoment-generating functionComputer scienceMathematical analysisArtificial intelligenceBiologyEcologyPaleontologyStatistical Distribution Estimation and ApplicationsBayesian Methods and Mixture ModelsProbabilistic and Robust Engineering Design
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