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

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题名:	An Improved Method of Predicting the Future: A Result on Improving the Stein-Rule Shrinkage Estimators of Regression Coefficients
作者:	Chang, Ching-Hui;Pal, Nabendu;Lin, Jyh-Jiuan;Lin, Jyh-Horng
贡献者:	淡江大學統計學系;淡江大學國際企業學系
关键词:	Quadratic loss;risk function;shrinkage estimation
日期:	1997-05-01
上传时间:	2009-11-30 12:57:05 (UTC+8)
出版者:	臺北縣：淡江大學未來學研究所
摘要:	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.
關聯:	Journal of futures studies=未來研究叢刊 1(2), pp.51-62
显示于类别:	[統計學系暨研究所] 期刊論文 [國際企業學系暨研究所] 期刊論文

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