New Generalized and Dual Generalized Order Statistics based Transmuted Log-Logistic Distributions

This paper introduces two extensions of the log-logistic distribution, namely the generalized order statistics transmuted log-logistic (GOSTLL) and the dual generalized order statistics transmuted log-logistic (DGOSTLL) distributions. These models are constructed based on the generalized and dual generalized order statistics based transmuted families of distributions. Some important statistical properties including reliability measures, hazard rate functions, entropies, etc. are studied. The maximum likelihood estimation of the parameters is presented for both of the new distributions. The usefulness of the proposed distributions is demonstrated through real data applications.

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Publication Details

Journal
Journal of Statistical Theory and Applications
Published
2026-01-07
DOI
https://doi.org/10.1007/s44199-025-00152-9
Primary Topic
Statistical Distribution Estimation and Applications
Type
article
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article

New Generalized and Dual Generalized Order Statistics based Transmuted Log-Logistic Distributions

Abdullah Almarashi, Manal Alharbi, Muhammad Qaiser Shahbaz
Journal of Statistical Theory and Applications
Statistical Distribution Estimation and Applications
article

New Generalized and Dual Generalized Order Statistics based Transmuted Log-Logistic Distributions

Abdullah Almarashi, Manal Alharbi, Muhammad Qaiser Shahbaz
article en

Abstract

This paper introduces two extensions of the log-logistic distribution, namely the generalized order statistics transmuted log-logistic (GOSTLL) and the dual generalized order statistics transmuted log-logistic (DGOSTLL) distributions. These models are constructed based on the generalized and dual generalized order statistics based transmuted families of distributions. Some important statistical properties including reliability measures, hazard rate functions, entropies, etc. are studied. The maximum likelihood estimation of the parameters is presented for both of the new distributions. The usefulness of the proposed distributions is demonstrated through real data applications.

Journal of Statistical Theory and ApplicationsVol. 25(1)
Qassim University (SA), King Abdulaziz University (SA)
Openalex Percentile: Top 95%
Statistical Distribution Estimation and Applications
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