On the Robust Rank Analysis of Linear Models with Nonsymetric Error Distributions.

Abstract

The robust analysis of linear models based on R-estimates involves an estimate of a scale parameter which is used in the analysis as a standardizing constant. The consistency of previous estimates of this scale parameter required that the underlying errors be symmetrically distributed. This assumption is not always warranted, for instance in survival models. A new estimate is proposed for the scale parameter and it is shown to be consistent for nonsymmetric and symmetric error distributions. With this new scale estimate, a complete robust analysis of a linear model can be accomplished without assuming symmetry. The small sample properties of the anlaysis are examined in a Monte Carlo study of several different situations.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1983
Accession Number
ADA135792

Entities

People

  • G. L. Sievers
  • J. W. Mckean

Organizations

  • Western Michigan University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Analysis Of Variance
  • Consistency
  • Data Science
  • Distribution Functions
  • Distribution Theory
  • Information Processing
  • Information Science
  • Probability
  • Signal Processing
  • Standards
  • Statistical Algorithms
  • Statistical Analysis
  • Statistical Inference
  • Statistics
  • Symmetry
  • United States

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Statistical inference.