On the Existence of Proper Bayes Minimax Estimators of the Mean of a Multivariate Normal Distribution.

Abstract

Consider the problem of estimating the mean of a multivariate normal distribution with covariance matrix the identity and sum of squared errors loss. In an earlier paper the author showed that if the dimension p is 5 or greater, then proper Bayes minimax estimators do exist. This result is reviewed briefly. The main purpose of the present paper is to show for p equal to 3 or 4, that there do not exist spherically symmetric proper Bayes minimax estimators. The author has been unable, thus far, to disprove the existence of a nonspherical proper Bayes minimax estimator for p equal 3 or 4. Of course, for p = 1,2, the usual estimator X bar is unique minimax but not proper Bayes. Bounds are derived for the possible bias of a minimax estimator. This result should be of some interest independent of its use in proving the main result of the paper. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jan 04, 1971
Accession Number
AD0716958

Entities

People

  • William E. Strawderman

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Covariance
  • Data Science
  • Estimators
  • Identities
  • Information Science
  • Mathematics
  • Normal Distribution
  • Statistical Algorithms
  • Statistical Analysis

Fields of Study

  • Mathematics

Readers

  • Fluid Dynamics.
  • Regression Analysis.