On the Discretization of the Weibull-G Family of Distributions: Properties, Parameter Estimates, and Applications of a New Discrete Distribution

In this article, we introduce a new three-parameter distribution called the discrete Weibull exponential (DWE) distribution, based on the use of a discretization technique for the Weibull-G family of distributions. This distribution is noteworthy, as its probability mass function presents both symmetric and asymmetric shapes. In addition, its related hazard function is tractable, exhibiting a wide range of shapes, including increasing, increasing–constant, uniform, monotonically increasing, and reversed J-shaped. We also discuss some of the properties of the proposed distribution, such as the moments, moment-generating function, dispersion index, Rényi entropy, and order statistics. The maximum likelihood method is employed to estimate the model’s unknown parameters, and these estimates are evaluated through simulation studies. Additionally, the effectiveness of the model is examined by applying it to three real data sets. The results demonstrate that, in comparison to the other considered distributions, the proposed distribution provides a better fit to the data.

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Publication Details

Journal
Symmetry
Published
2024-11-13
DOI
https://doi.org/10.3390/sym16111519
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

On the Discretization of the Weibull-G Family of Distributions: Properties, Parameter Estimates, and Applications of a New Discrete Distribution

Hadeel S. Klakattawi, Dawlah Alsulami, Abeer Balubaid
Symmetry
Statistical Distribution Estimation and Applications
article

On the Discretization of the Weibull-G Family of Distributions: Properties, Parameter Estimates, and Applications of a New Discrete Distribution

Hadeel S. Klakattawi, Dawlah Alsulami, Abeer Balubaid
article en

Abstract

In this article, we introduce a new three-parameter distribution called the discrete Weibull exponential (DWE) distribution, based on the use of a discretization technique for the Weibull-G family of distributions. This distribution is noteworthy, as its probability mass function presents both symmetric and asymmetric shapes. In addition, its related hazard function is tractable, exhibiting a wide range of shapes, including increasing, increasing–constant, uniform, monotonically increasing, and reversed J-shaped. We also discuss some of the properties of the proposed distribution, such as the moments, moment-generating function, dispersion index, Rényi entropy, and order statistics. The maximum likelihood method is employed to estimate the model’s unknown parameters, and these estimates are evaluated through simulation studies. Additionally, the effectiveness of the model is examined by applying it to three real data sets. The results demonstrate that, in comparison to the other considered distributions, the proposed distribution provides a better fit to the data.

SymmetryVol. 16(11)
King Abdulaziz University (SA)
Openalex Percentile: Top 79%
Statistical Distribution Estimation and Applications
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