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Journals / Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics / 2026 / Volume: 75 Issue: 2

The New Garima Distribution: Properties and Applications

Ayşe Metin Karakaş(BITLIS EREN UNIVERSITY)0000-0003-3552-0105
Fatma Bulut(BITLIS EREN UNIVERSITY)0000-0002-7684-6796
Pages
—
Publication Date
2026-02-09
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study introduces the Transmuted Half Logistic Garima (THLG) distribution, a novel and flexible model developed for analyzing lifetime data.
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Key Findings & 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.
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Conclusion & Impact: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.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Garima distribution · generalized family · characterizations

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.

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Cite This Article

Karakaş, A. M., Bulut, F. (2026). The New Garima Distribution: Properties and Applications. Communications Faculty of Sciences University of Ankara Series A1 Mathematics and Statistics, Volume: 75 Issue: 2. https://doi.org/10.31801/cfsuasmas.1642502

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References (14)

  1. Abebe, B., Tesfay, M., Eyob, T., and Shanker, R. (2019). A two-parameter power garima distribution with properties and applications. Annals of Biostatistics and Biometric Applications, 1(3):515.
  2. Aunali, A. S. and Venkatesan, D. (2019). Spc using the length biased weighted garima distribution. Science, Technology and Development Journal, pages 1–8.
  3. Balakrishnan, N. and Wong, K. H. T. (1991). Approximate mles for the location and scale parameters of the half-logistic distribution with type-ii right-censoring. IEEE Transactions on Reliability, 40(2):140– 145.
  4. Bjerkedal, T. (1960). Acquisition of resistance in guinea pigs infected with different doses of virulent tubercle bacilli. American Journal of Hygiene, 72(1):130–148.
  5. Chipepa, F., Moakofi, T., and Oluyede, B. (2022). The marshall–olkin odd power generalized weibull-g family of distributions with applications to covid-19 data. Journal of Probability and Statistical Science, 20(1):1–20.
  6. Cordeiro, G. M., Alizadeh, M., and Diniz Marinho, P. R. (2016). The type i half-logistic family of distributions. Journal of Statistical Computation and Simulation, 86(4):707–728.
  7. Hassan, A. S., Almetwally, E. M., and Ibrahim, G. M. (2021). Kumaraswamy inverted topp-leone distribution with applications to covid-19 data. Computers, Materials and Continua, 68(1):337–358.
  8. Krishnarani, S. D. (2019). On a power transformation of half-logistic distribution. Journal of Probability and Statistics, pages 1–10.
  9. Mohiuddin, M., Rather, A. A., Subramanian, C., and Dar, S. A. (2020). Transmuted garima distribution: Properties and applications. Journal of Xidian University, 14(3):112–123.
  10. Muhammad, M. and Liu, L. (2019). A new extension of the generalized half logistic distribution with applications to real data. Entropy, 21(4):339–376.
  11. Olapade, A. K. (2003). On characterizations of the half logistic distribution. InterStat, (2):1–7.
  12. Shanker, R. (2016). Garima distribution and its application to model behavioral science data. Biometrics and Biostatistics International Journal, 4(7):1–9.
  13. Shanker, R., Shukla, K. K., Sium, S., Welday, D., and Shanker, R. (2019). A quasi garima distribution. Journal of Applied Quantitative Methods, 14(1):27–44.
  14. Tahani, A. (2011). Estimation of the unknown parameters for the compound rayleigh distribution based on progressive first-failure-censored sampling. Open Journal of Statistics, 1(3):161–171.