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.
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Karakaş et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69d893c96c1944d70ce04c36 — DOI: https://doi.org/10.31801/cfsuasmas.1642502
Ayşe Metin Karakaş
Fatma Bulut
Communications Faculty Of Science University of Ankara Series A1Mathematics and Statistics
Bitlis Eren University
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