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.

Highlights

  • Among the existing distributions with support over the unit interval, the so-called Topp-Leone distribution, introduced by [1], is one of the most useful

  • Thanks to the structure of the TIIPTL-G family, we significantly increase the practical properties of the inverse exponential distribution

  • We provide some distributional results on order statistics in the setting of the TIIPTL-G

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Summary

Introduction

Among the existing distributions with support over the unit interval, the so-called Topp-Leone distribution, introduced by [1], is one of the most useful. In the recent years, the Topp-Leone distribution reveals to be efficient to define general families of distributions enjoying nice properties, including a great ability to model different practical data sets. For the purposes of this paper, let us describe the general family introduced by [23] It is based on the so-called power Topp-Leone distribution defined with the cdf and pdf given by, respectively, F∗ ( x; α, β) = x αβ (2 − x β )α , and x ∈ (0, 1). Thanks to the structure of the TIIPTL-G family, we significantly increase the practical properties of the inverse exponential distribution (more flexible shapes for the corresponding pdf, hrf, mode, skewness, kurtosis, etc.).

Important Functions
Asymptotes and Shapes
The TIIPTLIEx Distribution
Quantile Function
Mixture Representation
Moments and Central Moments
Incomplete Moments
Stochastic Ordering
Reliability
Order Statistics
Estimation and Simulation
Maximum Likelihood Method of Estimation
Percentile Method of Estimation
Right-Tail Anderson-Darling Method of Estimation
A Simulation Study
Applications
Findings
Conclusions
Full Text
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