An Improved Method of Predicting the Future: A Result on Improving the Stein-Rule Shrinkage Estimators of Regression Coefficients

機構典藏 > College of Business and Management > Graduate Institute & Department of Statistics > Journal Article > Item 987654321/20702

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/20702

Title:	An Improved Method of Predicting the Future: A Result on Improving the Stein-Rule Shrinkage Estimators of Regression Coefficients
Authors:	Chang, Ching-Hui;Pal, Nabendu;Lin, Jyh-Jiuan;Lin, Jyh-Horng
Contributors:	淡江大學統計學系;淡江大學國際企業學系
Keywords:	Quadratic loss;risk function;shrinkage estimation
Date:	1997-05-01
Issue Date:	2009-11-30 12:57:05 (UTC+8)
Publisher:	臺北縣：淡江大學未來學研究所
Abstract:	A major use of linear regression models is to predict the future. An improved shrinkage estimator of the regression coefficients leads to a better of the dependent (response) variable in terms of lower Prediction mean squared error. Therefore, in this paper we consider the Problem of improved estimation of the unknown coefficients of a linear Regression model under usual normality assumption. It is well known that the ordinary least squares (OLS) estimator of the regression coefficients can be dominated by the Stein-rule estimators which are again dominated by their "Positive-part" versions. In this paper we show that the estimators can be dominated by a new type of estimators which are quite different from the "positive-part" estimators.
Relation:	Journal of futures studies=未來研究叢刊 1(2), pp.51-62
Appears in Collections:	[Graduate Institute & Department of Statistics] Journal Article [Graduate Institute & Department of International Business] Journal Article

Files in This Item:

File	Size	Format
An Improved Method of Predicting the Future A Result on Improving the Stein-Rule Shrinkage Estimators of Regression Coefficients.pdf	909Kb	Adobe PDF	2	View/Open
index.html	0Kb	HTML	254	View/Open
index.html	0Kb	HTML	143	View/Open