Generalized Bayes minimax estimators of location vectors for spherically symmetric distributions with residual vector

Dominique Fourdrinier (), Othmane Kortbi () and William Strawderman ()

Metrika: International Journal for Theoretical and Applied Statistics, 2014, vol. 77, issue 2, 285-296

Abstract: We consider estimation of the mean vector, $$\theta $$ , of a spherically symmetric distribution with known scale parameter under quadratic loss and when a residual vector is available. We show minimaxity of generalized Bayes estimators corresponding to superharmonic priors with a non decreasing Laplacian of the form $$\pi (\Vert \theta \Vert ^{2})$$ , under certain conditions on the generating function $$f(\cdot )$$ of the sampling distributions. The class of sampling distributions includes certain variance mixtures of normals. Copyright Springer-Verlag Berlin Heidelberg 2014

Keywords: Spherical symmetry; Bayes estimators; Minimax estimators; Quadratic loss (search for similar items in EconPapers)
Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:spr:metrik:v:77:y:2014:i:2:p:285-296

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DOI: 10.1007/s00184-013-0437-9

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