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

Dominique Fourdrinier; Othmane Kortbi; William E. Strawderman

doi:10.1007/s00184-013-0437-9

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

Dominique Fourdrinier
, Othmane Kortbi
, William E. Strawderman

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

We consider estimation of the mean vector, θ, 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 π(||θ||2), under certain conditions on the generating function f (·) of the sampling distributions. The class of sampling distributions includes certain variance mixtures of normals.

Original language	English
Pages (from-to)	285-296
Number of pages	12
Journal	Metrika
Volume	77
Issue number	2
DOIs	https://doi.org/10.1007/s00184-013-0437-9
Publication status	Published - Apr 11 2013
Externally published	Yes

Keywords

Bayes estimators
Minimax estimators
Quadratic loss
Spherical symmetry

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty

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10.1007/s00184-013-0437-9

Cite this

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abstract = "We consider estimation of the mean vector, θ, 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 π(||θ||2), under certain conditions on the generating function f (·) of the sampling distributions. The class of sampling distributions includes certain variance mixtures of normals.",

keywords = "Bayes estimators, Minimax estimators, Quadratic loss, Spherical symmetry",

author = "Dominique Fourdrinier and Othmane Kortbi and Strawderman, \{William E.\}",

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AU - Fourdrinier, Dominique

AU - Kortbi, Othmane

AU - Strawderman, William E.

N1 - Publisher Copyright: © Springer-Verlag Berlin Heidelberg 2013.

PY - 2013/4/11

Y1 - 2013/4/11

N2 - We consider estimation of the mean vector, θ, 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 π(||θ||2), under certain conditions on the generating function f (·) of the sampling distributions. The class of sampling distributions includes certain variance mixtures of normals.

AB - We consider estimation of the mean vector, θ, 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 π(||θ||2), under certain conditions on the generating function f (·) of the sampling distributions. The class of sampling distributions includes certain variance mixtures of normals.

KW - Bayes estimators

KW - Minimax estimators

KW - Quadratic loss

KW - Spherical symmetry

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UR - https://www.scopus.com/pages/publications/85028166162#tab=citedBy

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EP - 296

JO - Metrika

JF - Metrika

IS - 2

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

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