Further Study of Robustification via A Bayesian Approach.

Abstract

A Bayesian model has been proposed which describes the generation of an observation by a process whereby with prior probability 1-alpha the usually assumed statistical structure is correct but with small probability alpha it is incorrect (for example, the observation has a very large variance). For a simple location estimate the nature of the down weighting of outlying observations produced by this model is studied and is compared with that of the presently popular M-estimators.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1979
Accession Number
ADA079733

Entities

People

  • George E. P. Box
  • Gina Chen

Organizations

  • University of Wisconsin–Madison

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Bayesian Inference
  • Bayesian Networks
  • Computational Science
  • Data Science
  • Estimators
  • Factorial Design
  • Information Science
  • Mathematics
  • Normal Distribution
  • Observation
  • Probability
  • Residuals
  • Standards
  • Statistical Analysis
  • Statistics
  • United States
  • Weighting Functions

Fields of Study

  • Mathematics

Readers

  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference