Quasi Lindley Regression Model Residual Analysis for Biomedical Data
The current study proposes and presents a new regression model for the response variable following the Quasi Lindley Regression. 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). In addition, a residual analysis is performed for the proposed regression model. The log- Quasi Lindley Regression model is compared to several other models, including Lindley regression and gamma regression, using various statistical criteria. The results show that the suggested model fits the data better than these other models. The model is expected to have applications in fields such as economics, biological studies, mortality and recovery rates, health, hazards, measuring sciences, medicine, and engineering.
Authors
- Ahmed Salih
- Wafaa Jaafar Hussein
Institutions
- University of Wasit (IQ)
Publication Details
- Journal
- Statistics Optimization & Information Computing
- Published
- 2025-06-12
- DOI
- https://doi.org/10.19139/soic-2310-5070-2649
- Primary Topic
- Advanced Statistical Methods and Models
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Đại học Quốc gia Hà Nội