会议专题

The Numerical Simulation of Improving Parameter Estimation by Instrumental Variable Method

In this paper the stochastic explanatory variables problem is studied using Monte-Carlo method.Taking a linear regression model with intercept of 3, slope of 4 as an example, whose random error in standard normal distribution, it is verified that parameter estimators are biased, especially the average relative error of estimator of slope is significantly large, as more than 10%, when random explanatory variables are in different contemporaneously correlated with random error item.When the instrumental variables, independent with random error item and in varying degrees related to random explanatory variable, is used, the estimation accuracy of the slope are significantly improved and the relative error dropped to less than 4%, but the estimation accuracy of the intercept term no significant improvement using the instrumental variable method.

stochastic explanatory variables Monte-Carlo method instrumental variable method linear regression model

WANG Yinao RUAN Aiqing ZHAN Zhihui

College of Mathematics & Information Science Wenzhou City,P.R.China 325035 City College Wenzhou University Wenzhou City,P.R.China 325035 College of Mathematics & Information Science Wenzhou University Wenzhou City,P.R.China 325035

国际会议

2011 IEEE International Conference on Grey System and Intelligent Services Joint with the 15th WOSC International Congress on Cybernetics and System(2011 IEEE灰色系统与智能服务国际会议暨系统与控制世界组织第15届年会)

南京

英文

820-824

2011-09-15(万方平台首次上网日期,不代表论文的发表时间)