Robust Estimation Techniques for Location Parameter Estimation of Symmetric Distributions

Abstract

Several robust estimators are considered for analysis and explanation. Monte Carlo techniques are used to investigate the efficiency of these robust estimators relative to the best estimator for the distribution under consideration. Sample sizes of 12 and 24 were drawn 4200 times from five symmetric probability distributions. The results show that over a class of distributions the robust estimators provide a higher guaranteed efficiency than the best estimator for any particular distribution in the family. Some interesting results are apparent from an analysis of the graphs in Appendix C indicating some upper bounds on the size of the Monte Carlo sample when conducting this type of study.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1972
Accession Number
AD0744695

Entities

People

  • John Caso

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • C4I
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Force
  • Applied Mathematics
  • Data Science
  • Information Science
  • Mathematics
  • New York
  • Normal Distribution
  • Operations Research
  • Order Statistics
  • Probability
  • Probability Distributions
  • Standards
  • Statistical Algorithms
  • Statistical Inference
  • Surveys
  • Systems Analysis
  • United States

Fields of Study

  • Mathematics

Readers

  • Statistical inference.
  • Theoretical Analysis.