Robust Improvement in Estimation of a Mean Matrix in an Elliptically Contoured Distribution

In estimation of a matrix of regression coefficients in a multivariate linear regression model, this paper shows that minimax and shrinkage estimators under a normal distribution remain robust under an elliptically contoured distribution. The robustness of the improvement is established for both invariant and noninvariant loss functions in the above model as well as in the growth curve model.

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Year of publication:	2001
Authors:	Kubokawa, T. ; Srivastava, M. S.
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 76.2001, 1, p. 138-152
Publisher:	Elsevier
Subject:	elliptically contoured distribution \| robustness of improvement \| multivariate linear model \| growth curve model \| regression coefficient matrix \| shrinkage estimation \| statistical decision theory \| point estimation

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005221392