A Decision Theoretic Approach to a Stochastic Approximation Problem.

Abstract

The problem of approximating the root of a linear function with unit slope is investigated. The error random variables are assumed to be independent and identically distributed standard normal random variables. A stochastic approximation procedure is characterized as a sequence of decision functions corresponding to a particular sequence of statistical decision problems. Bayes procedures are characterized and convergence is proved. The harmonic Robbins-Monro procedure is shown to correspond to a sequence of 'natural' decision functions. A more general approximation problem is also considered. (Author)

Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1968
Accession Number
AD0842318

Entities

People

  • Donald L. Evans

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Convergence
  • Random Variables
  • Sequences
  • Standards

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Mathematical Modeling and Probability Theory.
  • Regression Analysis.