An Extended Alpha Power Family of Distributions: Its Applications to the Scientific Data

In this study, a Novel Extended Alpha Power (NEAP) family of distributions is introduced to improve efficiency of the existing class of lifetime distributions. A sub-mode of NEAP is further studied using Weibull distribution as an input model. This new version of distribution is referred as novel extended alpha power Weibull (NEAPW) distribution. The new distribution is suitable for modeling both monotone and non-monotone type data. Various statistical characteristics of the suggested model are estimation of parameters, the order statistics, mean residual, quantile function, and moments are obtained. A simulation study of the novel distribution is also conducted. The usefulness and effectiveness of the novel model is established by investigating two real data sets from the field of basic sciences.

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Publication Details

Journal
International Journal of Analysis and Applications
Published
2025-06-09
DOI
https://doi.org/10.28924/2291-8639-23-2025-134
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
Field-Weighted Citation Impact
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article

An Extended Alpha Power Family of Distributions: Its Applications to the Scientific Data

Mohammad Abiad, Noor Saeed Khan, Ihtisham ul Haq, Muhammad Shafiq et al.
International Journal of Analysis and Applications
Statistical Distribution Estimation and Applications
article

An Extended Alpha Power Family of Distributions: Its Applications to the Scientific Data

Mohammad Abiad, Noor Saeed Khan, Ihtisham ul Haq, Muhammad Shafiq, Alamgir
article en

Abstract

In this study, a Novel Extended Alpha Power (NEAP) family of distributions is introduced to improve efficiency of the existing class of lifetime distributions. A sub-mode of NEAP is further studied using Weibull distribution as an input model. This new version of distribution is referred as novel extended alpha power Weibull (NEAPW) distribution. The new distribution is suitable for modeling both monotone and non-monotone type data. Various statistical characteristics of the suggested model are estimation of parameters, the order statistics, mean residual, quantile function, and moments are obtained. A simulation study of the novel distribution is also conducted. The usefulness and effectiveness of the novel model is established by investigating two real data sets from the field of basic sciences.

International Journal of Analysis and ApplicationsVol. 23
Openalex Percentile: Top 87%
Statistical Distribution Estimation and Applications
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