Regression Model for gamma Lindley distribution with Application

Regression Model for gamma Lindley distribution

  • Asaad Mohammed Al-Doori Department of Applied Statistics and Econometrics, Faulty of Graduate Studies for Statistical Research, Cairo University, Cairo, Egypt.
  • Salah M Mohammed Department of Applied Statistics and Econometrics, Faulty of Graduate Studies for Statistical Research, Cairo University, Cairo, Egypt.
  • Amal Mohammed Abdelfattah Department of Applied Statistics and Econometrics, Faulty of Graduate Studies for Statistical Research, Cairo University, Cairo, Egypt.
DOI: https://doi.org/10.19139/soic-2310-5070-3476
Keywords: Definition of gamma Lindley distribution, Gamma Lindley regression, Residual analysis, Deviance and martingale residual

Abstract

The present study introduces a novel regression model where the response variable follows the gamma Lindley distribution. The model's unknown parameters are estimated using the maximum likelihood method. To assess the effectiveness of these estimates, a simulation study is carried out. Furthermore, a residual analysis is conducted to examine the proposed model's adequacy. The gamma Lindley model is compared with other regression models, such as Weibull and gamma regression, based on various statistical criteria. The findings indicate that the proposed model provides a superior fit to the data compared to the alternatives. The model is expected to be applicable in diverse fields, including economics, biological research, mortality and recovery analysis, health studies, hazard assessment, measurement sciences, medicine, and engineering.
Published
2026-03-11
How to Cite
Al-Doori, A., Mohammed, S., & Abdelfattah, A. (2026). Regression Model for gamma Lindley distribution with Application. Statistics, Optimization & Information Computing. https://doi.org/10.19139/soic-2310-5070-3476
Issue
Online First
Section
Research Articles
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