Adaptive Robust Estimation of Location and Scale Parameters of Symmetric Populations.

Abstract

Critical values of several criteria, for equal Type I and Type II error rates (probabilities of misclassification), have now been established for sample sizes n = 8 (4) 24 by means of a Monte Carlo study based on 5000 random samples of each size from each of the above populations Uniform (U), Normal (N), and Double (D). Mean square errors of the adaptive estimates are compared with those of the ML estimates if the population from which each sample came is known, and the effect of debiasing the ML estimates of the standard deviation (sigma) is studied. Adaptive estimation of the canonical scale parameter F sigma, where the factor F is defined as the multiplier of sigma such that F sigma is the 97.5% point of a population symmetric about zero, is also considered. Monte Carlo studies have also been conducted to determine the performance of the various criteria when applied to an independent set of random samples (obtained by using a different seed for the random number generator) from U, N and D and to random samples from several other symmetric populations, for the above values of n and for the intermediate values n = 10 (4) 22, with critical values of the criteria determined by interpolation.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1978
Accession Number
ADA062436

Entities

People

  • Albert H. Moore
  • H. Leon Harter
  • Thomas F. Curry

Organizations

  • Flight Dynamics Laboratory

Tags

Communities of Interest

  • Human Systems

DTIC Thesaurus Topics

  • Aeronautical Laboratories
  • Air Force
  • Air Force Facilities
  • Classification
  • Computers
  • Data Science
  • Estimators
  • Information Science
  • Maximum Likelihood Estimation
  • Military Personnel
  • Order Statistics
  • Probability
  • Probability Density Functions
  • Random Variables
  • Standards
  • Statistical Algorithms
  • Statistical Samples

Fields of Study

  • Mathematics

Readers

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