Biased estimators in beta regression model in the presence of Multicollinearity | ||
| College Of Basic Education Research Journal | ||
| Volume 19, Issue 3, September 2023, Pages 652-665 PDF (516.9 K) | ||
| Document Type: Research Paper | ||
| DOI: 10.33899/berj.2023.180672 | ||
| Author | ||
| Ghada Yousef* | ||
| Departmet of Mechanical Technology, Technical Institute in Mosul, Northern Technical University | ||
| Abstract | ||
| In regression modeling, the occurrence of a strong correlation among predictors has negative consequences for regression estimation. This problem can be solved using a variety of biased methods. From the generalized linear models, the beta regression model is a subset. When the response variable under examination is percentage, the beta regression model is a well-known model in research. Using various theories, a number of biased estimators for overcoming multicollinearity in beta regression models have been developed in the literature. There is a review of recent biased techniques for beta regression models. We can learn more about the performance of these biased estimators by comparing them. | ||
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