CONTRIBUTIONS TO ROBUST ESTIMATION,

Abstract

For the problem of efficiency-robust estimation of the location parameter theta of a family of symmetric pdf's f(x-theta(vertical line) lambda), lambda epsilon Lambda = (1,...,m), theta epsilon Theta = (theta such that minus infinity < theta < infinity), the method of 'mixture models' of Birnbaum is applied to determine generalized Pitman estimators, which are shown to be admissible, with squared error loss function, under broad regularity conditions. With increasing sample size, these estimators are proved to be fully efficient (i.e., asymptotically equivalent, for each value of lambda, to the maximum likelihood estimator which would be appropriate if the true value of lambda were known). Computationally tractable analogous estimators based on k sample quantiles are defined in the context of the model representing their asymptotic normal distributions. It is shown that with increasing k these approach equivalence to the fully efficient estimators based on complete samples. Equivalent estimators are given also for the case of unknown scale parameters. Efficiency-robust linear unbiased estimators based on sample quantiles are derived and the optimal spacing of quantiles is discussed. (Author)

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1967
Accession Number
AD0661353

Entities

People

  • Valerie Mike

Organizations

  • New York University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Distribution Functions
  • Efficiency
  • Estimators
  • Mathematics
  • Normal Distribution

Fields of Study

  • Mathematics

Readers

  • Analytical Mechanics
  • Statistical inference.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • AI & ML - Neural Networks
  • Space