A Special Purpose Linear Programming Algorithm for Obtaining Least Absolute Value Estimators in a Linear Model with Dummy Variables.

Abstract

Dummy (0, 1) variables are frequently used in statistical modeling to represent the effect of certain extraneous factors. This paper presents a special purpose linear programming algorithm for obtaining least-absolute-value estimators in a linear model with dummy variables. The algorithm employs a compact basis inverse procedure and incorporates the advanced basis exchange techniques available in specialized algorithms for the general linear least-absolute-value problem. Computational results with a computer code version of the algorithm are given. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1977
Accession Number
ADA056762

Entities

People

  • Edward Frome
  • Ronald D. Armstrong

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Computers
  • Data Analysis
  • Data Science
  • Equations
  • Estimators
  • Heuristic Methods
  • Information Science
  • Iterations
  • Light Armored Vehicles
  • Linear Programming
  • New York
  • Regression Analysis
  • Simplex Method
  • Statistical Algorithms
  • United States

Fields of Study

  • Mathematics

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