Least Absolute Value Estimators for One-Way and Two-Way Tables.

Abstract

This paper concerns itself with the problem of estimating the parameters in a one-way and two-way classification model by minimizing the sum of the absolute deviations of the regression function from the observed points. The one-way model reduces to obtaining a set of medians from which optimal parameters can be obtained by simple arithmetic manipulations. The two-way model is transformed into a specially structured linear programming problem and two algorithms are presented to solve this problem. The occurrence of alternative optimal solutions in both models is discussed, and numerical examples are presented. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1976
Accession Number
ADA031399

Entities

People

  • E. L. Frome
  • R. D. Armstrong

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Arithmetic
  • Classification
  • Computations
  • Computer Programming
  • Computers
  • Data Analysis
  • Elections
  • Estimators
  • Linear Programming
  • Nebraska
  • Numerical Analysis
  • Random Variables
  • Regression Analysis
  • Simplex Method
  • Statistics
  • United States

Fields of Study

  • Mathematics

Readers

  • Marine Propulsion Engineering and Naval Architecture
  • Operations Research
  • Statistical inference.