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Unbiased Estimation of the MSE Matrix of Stein-Rule Estimators, Confidence Ellipsoids, and Hypothesis Testing

Published online by Cambridge University Press:  11 February 2009

R.A.L. Carter
Affiliation:
University of Western Ontario
M.S. Srivastava
Affiliation:
University of Toronto
V.K. Srivastava
Affiliation:
Lucknow University
A. Ullah
Affiliation:
University of Western Ontario

Abstract

We first present an unbiased estimator of the MSE matrix of the Stein-rule estimator of the coefficient vector in a normal linear regression model. The Steinrule estimator can be used with both its estimated MSE matrix and with the least-squares MSE matrix to form confidence ellipsoids. We derive the approximate expected squared volumes and coverage probabilities of these confidence sets and discuss their ranking. These results can be applied to the conditional prediction of the mean of the endogenous variable. We also consider the power of F-tests which employ the Stein-rule estimator in place of the least-squares estimator.

Type
Articles
Copyright
Copyright © Cambridge University Press 1990

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References

1.Aigner, D.J. & Judge, G.G.. Application of pre-test and Stein estimators to economic data. Econometrica 45 (1977): 12791288.Google Scholar
2.Berger, J.A robust generalized Bayes estimator and confidence region for a multivariate normal mean. The Annals of Statistics 8 (1980): 716761.Google Scholar
3.Chi, S. & Judge, G.G.. On assessing the precision of Stein's estimator. Economics Letters 18 (1985): 143148.CrossRefGoogle Scholar
4.Hill, R.C. & Fomby, T.B.. Improved confidence sets in a non-Utopian setting. In Slottje, D.J. (ed.), Advances in Econometrics, 5: Innovations in Quantitative Methods: Essays in Honor of Robert L. Basmann, JAI Press, 1986.Google Scholar
5.Hwang, J.T. & Casella, G.. Minimax confidence sets for the mean of a multivariate normal distribution. The Annals of Statistics 10(1982): 868881.Google Scholar
6.Joshi, V.M.Inadmissability of the usual confidence sets for the mean of a multivariate normal population. Annals of Mathematical Statistics 38 (1967): 18681875.CrossRefGoogle Scholar
7.Judge, G.G. & Bock, M.E.. The statistical implication of pre-test and Stein-rule estimators in econometrics. New York: North-Holland, 1978.Google Scholar
8.Menjoge, S.S.On double fc-class estimators of coefficients in linear regressions. Economics Letters 15 (1984): 295300.CrossRefGoogle Scholar
9.Phillips, P.C.B.The exact distribution of the Stein-rule estimator. Journal of Econometrics 25 (1984): 123132.Google Scholar
10.Rao, C.R.Linear statistical inference and its applications. New York: Wiley, 1973.Google Scholar
11.Stein, CM. Estimation of the mean of a multivariate normal distribution. The Annals of Statistics 9 (1981): 11351167.Google Scholar
12.Ullah, A. & Giles, D.E.A.. The positive-part Stein-rule estimator and tests of hypotheses. Economics Letters 26 (1988): 4952.CrossRefGoogle Scholar
13.Ullah, A. & Ullah, S.. Double k-class estimators of coefficients in linear regression. Econometrica 46 (1978): 705722.Google Scholar
14.Vinod, H.D. & Ullah, A.. Recent advances in regression methods. New York: Marcel Dekker, 1981.Google Scholar