Title of article
Robust shrinkage estimation for elliptically symmetric distributions with unknown covariance matrix
Author/Authors
Fourdrinier، نويسنده , , Dominique and Strawderman، نويسنده , , William E. and Wells، نويسنده , , Martin T.، نويسنده ,
Issue Information
دوفصلنامه با شماره پیاپی سال 2003
Pages
16
From page
24
To page
39
Abstract
Let X,V1,…,Vn−1 be n random vectors in Rp with joint density of the formf(X−θ)′Σ−1(X−θ)+∑j=1n−1 Vj′Σ−1Vj,where both θ and Σ are unknown. We consider the problem of the estimation of θ with the invariant loss (δ−θ)′Σ−1(δ−θ) and propose estimators which dominate the usual estimator δ0(X)=X simultaneously for the entire class of such distributions. The proof involves the development of expressions which are analogous to unbiased estimators of risk and which in fact reduce to unbiased estimators of risk in the normal case. The method is applicable to the case where Σ is structured. As an example, we examine the case where Σ is diagonal.
Keywords
Robustness , James–Stein estimation , elliptically symmetric distributions , minimax , Risk function , Unknown covariance , Quadratic loss , Location parameter
Journal title
Journal of Multivariate Analysis
Serial Year
2003
Journal title
Journal of Multivariate Analysis
Record number
1557868
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