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 journalArticlepeer-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 languageEnglish
Pages (from-to)285-296
Number of pages12
JournalMetrika
Volume77
Issue number2
DOIs
Publication statusPublished - Apr 11 2013
Externally publishedYes

Keywords

  • Bayes estimators
  • Minimax estimators
  • Quadratic loss
  • Spherical symmetry

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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