CONVERGENCE RATES FOR EMPIRICAL BAYES TWO-ACTION PROBLEMS II. CONTINUOUS CASE.

Abstract

A sequence of decision problems is considered where for each problem the observation has a probability density function of exponential type with parameter lambda where lambda is selected independently for each problem according to an unknown prior distribution G(lambda). It is supposed that in each of the problems, one of two possible actions (e.g., 'accept' or 'reject') must be taken. Under various assumptions, reasonably sharp upper bounds are found for the rate at which the risk of the nth problem approaches the smallest possible risk for certain refinements of the standard empirical Bayes procedures. For suitably chosen procedures, under situations likely to occur in practice, rates faster than n to the power (-1 + epsilon) may be obtained for arbitrarily small epsilon > 0. Arbitrarily slow rates can occur in pathological situations. (Author)

Document Details

Document Type
Technical Report
Publication Date
Nov 20, 1967
Accession Number
AD0661251

Entities

People

  • J. Van Ryzin
  • M. V. Johns Jr.

Organizations

  • Stanford University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Convergence
  • Data Science
  • Information Science
  • Mathematics
  • Observation
  • Probability
  • Probability Density Functions
  • Random Variables
  • Sequences
  • Standards

Fields of Study

  • Mathematics

Readers

  • Analytical Mechanics
  • Statistical inference.
  • Systems Analysis and Design