Abstract
This study introduces the Transmuted Half Logistic Garima (THLG) distribution, a novel and flexible model developed for analyzing lifetime data. The THLG distribution extends the Garima distribution by applying the Half Logistic generator to its cumulative distribution function, enhancing its ability to model a wider range of data patterns, including various shapes and hazard rate behaviors. We investigate the statistical properties of the THLG distribution in detail and estimate its parameters using the method of maximum likelihood estimation (MLE). To assess the performance of the proposed estimators, a Monte Carlo simulation study is conducted. Furthermore, the applicability of the THLG distribution is demonstrated through the analysis of three real-world datasets. The findings show that the THLG distribution outperforms several well-known lifetime distributions, highlighting its potential as a robust tool for reliability and survival analysis.
Keywords
Garima distribution generalized family characterizations lifetime data reliability analysis
Ethical Statement
Since the article does not contain any studies with human or animal subjects, its approval by the ethics committee was not required.
Supporting Institution
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References
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Details
| Primary Language | English |
|---|---|
| Subjects | Statistical Data Science, Applied Statistics, Statistics (Other) |
| Journal Section | Research Article |
| Authors | |
| Submission Date | February 18, 2025 |
| Acceptance Date | September 19, 2025 |
| Early Pub Date | February 9, 2026 |
| Publication Date | February 9, 2026 |
| IZ | https://izlik.org/JA97YD46KN |
| Published in Issue | Year 2026 Issue: Advanced Online Publication |
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Aim & Scope
Aim
Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics (Commun. Fac. Sci. Univ. Ank. Ser. A1. Math. Stat.) is an international peer-reviewed journal dedicated to the publication of high-quality research articles in all areas of pure and applied mathematics and statistics. The journal aims to provide a platform for the dissemination of original and significant contributions that advance theoretical understanding and practical applications in these fields.
Scope
The scope of Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics includes, but is not limited to:
- Pure mathematics: algebra, analysis, geometry, topology, number theory, mathematical logic, fuzzy logic
- Applied mathematics: numerical analysis, optimization, differential equations, mathematical physics, mathematical modeling
- Probability and statistics: theoretical statistics, statistical modeling, data analysis, stochastic processes, biostatistics, operation research, and econometrics
- Interdisciplinary research that connects mathematics or statistics with other scientific disciplines such as machine learning, pattern recognition, clustering etc.
The journal welcomes both theoretical developments and innovative applications. It supports the exchange of ideas among researchers worldwide and encourages submissions that bridge the gap between theory and practice.
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Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics journal primarily targets researchers, academics, postgraduate, and doctoral students working in the fields of mathematics and statistics, as well as anyone interested in staying updated on current developments in these disciplines. The articles we publish are particularly relevant to specialists in the following areas:
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Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics
