A Conditional Property of Adaptive Estimators.

Abstract

In adaptive estimation, it is often considered that an estimator has made a mistake if the component estimator chosen for use is not the most efficient for the distribution sampled. Theoretical and simulation results point to a fallacy in this line of thought. The Monte Carlo study involves extension of the Princeton Swindle to distributions conditional on a location-and scale free statistic, and to the uniform. The results give a partial explanation for the sometimes surprising robustness of adaptive L-estimators. (Author)

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jul 25, 1979
Accession Number
ADA072991

Entities

People

  • William C. Parr

Organizations

  • Southern Methodist University

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Computer Simulations
  • Contracts
  • Data Science
  • Estimators
  • Governments
  • Information Science
  • Military Research
  • Monte Carlo Method
  • Order Statistics
  • Sampling
  • Simulations
  • Statistics
  • United States
  • United States Government
  • Universities

Fields of Study

  • Mathematics

Readers

  • Statistical inference.
  • Theoretical Analysis.