Some one and two parameter estimators for the multicollinear gaussian linear regression model: simulations and applications
Surveys in Mathematics and its Applications(2023)
摘要
The ordinary least square estimator is inefficient when there exists multicollinearity among regressors in linear regression model. There are many methods available in literature to solve the multicollinearity problem. In this study, we consider some one and two parameter estimators for estimating the regression parameters. We theoretically compared the estimators in terms of smaller mean squared error (MSE) criteria. A Monte Carlo simulation study has been conducted to compare the performance of the estimators numerically. Finally, for illustration purposes, a real-life data is analyzed.
更多查看译文
关键词
d estimator,linear regression model,mse,multicollinearity,ridge regression estimator,james-stein estimator,liu estimator,modified liu estimator,simulation study
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要