Bayes Risk for the Test of Location-The Infinite Dimensional Case.

Abstract

Let X(1), X(2) be independent normal with mean vector theta and covariance matrix I. Let the null hypothesis be normal with zero mean and covariance matrix sigma. Quadratic loss (theta primed A theta) and constant loss are considered. Rubin and Sethuraman obtained asymptotic results for the above test in the case of a finite dimensional parameter space. New asymptotic results have been obtained for the case in which the parameter space is infinite dimensional. This development is motivated by the need to extend the Bayes Risk Efficiency analysis to time series problems and to problems in which the alternative hypothesis is a function space. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1972
Accession Number
AD0744965

Entities

People

  • Philip Cohen

Organizations

  • Purdue University

Tags

DTIC Thesaurus Topics

  • Computing-Related Activities
  • Covariance
  • Data Science
  • Efficiency
  • Information Science
  • Interdisciplinary Science
  • Mathematical Analysis
  • Mathematics

Fields of Study

  • Mathematics

Readers

  • Linear Algebra
  • Statistical inference.

Technology Areas

  • Space