On Estimating Variance of Robust Estimators when the Errors are Asymmetric.

Abstract

We investigate the effects of asymmetry on estimates of variance of robust estimator in location and regression problems, showing the heavy skewness of errors can seriously bias the common variance estimates for location and intercept, a problem that can be corrected by jackknifing for location but is more intractable for the intercept in regression. The scale parameters in regression seem not to be as seriously subject to this bias if the sample size is large compared to the number parameters. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1978
Accession Number
ADA072598

Entities

People

  • Raymond J. Carroll

Organizations

  • University of North Carolina at Chapel Hill

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Asymmetry
  • Data Science
  • Distribution Functions
  • Estimators
  • Information Science
  • North Carolina
  • Order Statistics
  • Probability
  • Random Number Generators
  • Random Variables
  • Sampling
  • Standards
  • Statistics
  • Two Dimensional
  • Universities

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Atmospheric Science / Meteorology, specifically Wind Wave Turbulence.
  • Explosive Engineering.