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The Statistical Consequences of Preliminary Test Estimators in Regression
M. E. Bock, T. A. Yancey and G. G. Judge
Journal of the American Statistical Association
Vol. 68, No. 341 (Mar., 1973), pp. 109-116
Stable URL: http://www.jstor.org/stable/2284154
Page Count: 8
You can always find the topics here!Topics: Estimators, Preliminary estimates, Statistical estimation, Statistical models, Estimators for the mean, Statistics, Regression analysis, Analytical estimating, Mathematical vectors, Parametric models
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This study is concerned with deriving the properties of the preliminary test estimator for the general linear normal regression model, ascertaining the characteristics of the risk functions over the parameter space, and determining the conditions necessary for the risk of this estimator to exceed or be less than the conventional one under squared error loss. A test procedure and the problem of choosing an optimal level of significance for the test are discussed. Some theorems and lemmas used in evaluating the risk and some properties of functions of the non-central F distribution are developed in the appendices.
Journal of the American Statistical Association © 1973 American Statistical Association