Min-Max Bias Robust M-Estimates of Scale.

Abstract

Min-max bias robust M-estimates of scale are obtained for positive random variables which have epsilon-contaminated distributions. Any such estimate is a scaled order statistic, with the order statistic determined by epsilon. As epsilon approaches limit of 0.5 the min-max bias robust estimate becomes a scaled sample median, which thereby enjoys both high breakdown point of 0.5 and min-max bias robustness. Furthermore, for a wide range of epsilon, min-max estimate is quite close to the scaled median in terms of both structure and min-max bias behavior. Results are also obtained for random variables whose distribution is F = (epsilon)sub 0 + epsilon H with F sub o symmetric about an unknown location parameter. In particular we show that when F sub o is normal and < or = epsilon < or = .35, the min-max bias M-estimate of scale is a scaled order statistic applied to the absolute value of centered data, with the median as the centering estimate. This estimate is extremely close to a scaled median absolute deviation about the median, in terms of both structure and bias behavior.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1986
Accession Number
ADA179255

Entities

People

  • R. D. Martin
  • Ruben H. Zamar

Organizations

  • University of Washington

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DTIC Thesaurus Topics

  • Construction
  • Contamination
  • Contracts
  • Distribution Functions
  • Efficiency
  • Estimators
  • Inequalities
  • Mathematics
  • Normal Distribution
  • Numbers
  • Optimal Estimators
  • Random Variables
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  • Time Series Analysis
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  • Approximation Theory.