The Log Akash Regression Model with Application

Authors

  • Samy Mohamed Department of Applied Statistics and Econometrics, Faulty of Graduate Studies for Statistical Research, Cairo University
  • Salah Mahdy Ramadan Department of Applied Statistics and Econometrics, Faulty of Graduate Studies for Statistical Research, Cairo University
  • Ahamed Hassan Youssef Department of Applied Statistics and Econometrics, Faulty of Graduate Studies for Statistical Research, Cairo University
  • Amal M. Abdelfattah Department of Applied Statistics and Econometrics, Faulty of Graduate Studies for Statistical Research, Cairo University

DOI:

https://doi.org/10.19139/soic-2310-5070-3290

Keywords:

Definition of Akash distribution, log Akash regression Model, Maximum Likelihood, Residual analysis, Deviance and martingale residual

Abstract

The current study proposes and presents a new regression model for the response variable following the Akashdistribution. The unknown parameters of the regression model are estimated using the maximum likelihood method. A simulation study is conducted to evaluate the performance of the maximum likelihood estimates (MLEs). Additionally, a residual analysis is performed for the proposed regression model. The log-Akash model is compared to several other models, including Weibull regression and gamma regression, using various statistical criteria. The results show that the suggested model fits the data better than these other models. It is anticipated that the model has applications in fields such as economics,biological studies, mortality and recovery rates, health, hazards, measuring sciences, medicine, and engineering.

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Published

2025-12-15

How to Cite

Mohamed, S., Mahdy Ramadan, S. ., Hassan Youssef, A., & M. Abdelfattah, A. . (2025). The Log Akash Regression Model with Application. Statistics, Optimization & Information Computing, 15(3), 1821–1833. https://doi.org/10.19139/soic-2310-5070-3290

Issue

Vol. 15 No. 3 (2026)

Section

Research Articles

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