Improved shrinkage estimation of squared multiple correlation coefficient and squared cross-validity coefficient

Gwowen Shieh*

*此作品的通信作者

研究成果: Article同行評審

56 引文 斯高帕斯(Scopus)

摘要

The sample squared multiple correlation coefficient is widely used for describing the usefulness of a multiple linear regression model in many areas of science. In this article, the author considers the problem of estimating the squared multiple correlation coefficient and the squared cross-validity coefficient under the assumption that the response and predictor variables have a joint multinormal distribution. Detailed numerical investigations are conducted to assess the exact bias and mean square error of the proposed modifications of established estimators. Notably, the positive-part Pratt estimator and the synthesis of Browne and positive-part Pratt estimators are recommended in the estimation of squared multiple correlation coefficient and squared cross-validity coefficient, respectively, for their overall advantages of incurring the least amount of statistical discrepancy and computational requirement.

原文English
頁(從 - 到)387-407
頁數21
期刊Organizational Research Methods
11
發行號2
DOIs
出版狀態Published - 4月 2008

指紋

深入研究「Improved shrinkage estimation of squared multiple correlation coefficient and squared cross-validity coefficient」主題。共同形成了獨特的指紋。

引用此