Estimators Shrinking towards Projection Vector for Multivariate Normal Mean Vector under the Norm with a Known Interval
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- James-Stein Type Estimators Sample Mean Projection Matrix
- Consider the problem of estimating a mean vector ( ), with a projection matrix under the quadratic loss, based on a sample . In this paper a James-Stein type estimator with shrinkage form is given when it's variance distribution is specified and when the norm is constrain, where is an idempotent and symmetric matrix and . It is characterized a minimal complete class of James-Stein type estimators in this case. And the subclass of James-Stein type estimators that dominate the sample mean is derived.
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