Representations of the Space of Distributions in Robust Estimation of Location.

Abstract

In many situations it is useful to have a low-dimensional representation of the space of distributions. In this report, one, two and three dimensional representations are given which are of particular relevance to the study of robust estimation of location based on rank estimators. The distances are defined as functions of the asymptotic relative efficiency of the most efficient rank estimator for one distribution when used on data from another distribution. Values of these distance functions are computed for a large number of pairs of distributions and multidimensional scaling is used to find the low-dimensional representations. (Author)

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Document Details

Document Type
Technical Report
Publication Date
May 01, 1981
Accession Number
ADA100562

Entities

People

  • Brian L. Joiner
  • David L. Hall

Organizations

  • University of Wisconsin–Madison

Tags

DTIC Thesaurus Topics

  • Contracts
  • Data Science
  • Efficiency
  • Estimators
  • Information Science
  • Materials
  • Mathematical Analysis
  • Mathematics
  • North Carolina
  • Probability
  • Statistical Analysis
  • Statistical Distributions
  • Statistics
  • Three Dimensional
  • United States
  • Universities
  • Wisconsin

Fields of Study

  • Mathematics

Readers

  • Distributed Systems and Data Platform Development
  • Statistical inference.

Technology Areas

  • Space