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Mean squared error matrix comparisons between biased estimators - an overview of recent results. (English) Zbl 0703.62066
Summary: We give a systematic report on mean squared error marix comparisons of competing biased estimators. Our approach is quite general: The parameter vector to be estimated is assumed to belong to a subset of the p- dimensional Euclidean space. However, to illustrate our results, we shall pay attention to the linear regression model where biased estimation is very popular. Especially we are interested in generalized ridge and restricted least squares estimation.
62H12Multivariate estimation
62J05Linear regression
62J07Ridge regression; shrinkage estimators
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