The Form, and Some Robustness Properties of Integrated Distance Estimators for Linear Models, Applied to Some Published Data Sets.

Abstract

A critical procedure for use in linear models is introduced and developed in some detail. It is based on a nonlinear analogue to the usual linear least squares procedure, more specifically, in the integrated distance between characteristic functions (densities) and their sample counterparts. Location and scale parameters are estimated simultaneously. The procedure depends on a user specified parameter which may be varied to determine the sensitively of the parameters and observational weights to such variation. A sensitivity analysis of this type is useful in isolating potential problems with the data or with the assumed model. When the procedure is employed with the user-oriented parameter held fixed, a robust procedure results. The statistical properties of this procedure are discussed in some detail. A number of illustrations, taken from the literature, are examined. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1982
Accession Number
ADA119728

Entities

People

  • A. S. Paulson
  • E. H. Nicklin

Organizations

  • Rensselaer Polytechnic Institute

Tags

Communities of Interest

  • C4I

DTIC Thesaurus Topics

  • Analysis Of Variance
  • Combinatorial Analysis
  • Computational Science
  • Data Analysis
  • Data Mining
  • Data Science
  • Estimators
  • Experimental Design
  • Gaussian Distributions
  • Information Science
  • Mathematical Models
  • Military Research
  • Models
  • Probability
  • Statistical Algorithms
  • Stochastic Processes
  • Two Dimensional

Fields of Study

  • Mathematics

Readers

  • Statistical inference.
  • Systems Analysis and Design