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- W2494582107 abstract "Let Z be a p-dimensional random vector distributed according to the multi-normal distribution with mean vector 9 and covariance matrix a2E, where a2 is unknown and E is a known positive definite matrix. Let L be the loss function defined by L(6, 0) = (6-0)'A(6-9), where A is a known symmetric positive definite matrix. A modified James-Stein estimator for 0 is obtained which dominates Z with respect to L for p > 3. This is used to get a modified estimator of P in the linear model: y=x'p+s, where e.N(O, a2), p =(pf1 . . ., p)' and x =(x1, . . ., xp)'. This modified estimator of P dominates the least squares estimator with respect to L for p > 3. When m( > p) sets of x-values are given, the modified estimator provides a better estimation of the m true y-values than the least squares estimator with respect to the squared error loss." @default.
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- W2494582107 date "1988-01-01" @default.
- W2494582107 modified "2023-09-23" @default.
- W2494582107 title "A modified James-Stein estimator with application to multiple regression analysis" @default.
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