Transforming Contingency Tables.

Abstract

We present a general theorem on transforming contingency tables and several applications where the transformation technique has allowed us to take advantage of the Iterative Proportional Fitting Procedure and has resulted in simple and useful procedures. A further advantage of this technique is that it is sometimes possible to recognize closed-form estimates in the transformed problem while they would be overlooked in the original setting. We shall view the estimation problem as one of minimizing the Kullback-Leibler information distance between two probability mass functions and will roughly follow the notation of Csiszar (1976). Although we have adopted the information distance point of veiw, the duality between maximum likelihood estimation and minimum information estimation (see e.g. Darroch and Ratcliff (1972)) implies that the results of this paper can just as well be interpreted from the maximum likelihood point of view.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1981
Accession Number
ADA104182

Entities

People

  • Michael M. Meyer

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Analysis Of Variance
  • Classification
  • Computer Programs
  • Data Analysis
  • Data Science
  • Equations
  • Geometry
  • Information Science
  • Maximum Likelihood Estimation
  • Notation
  • Probability
  • Probability Distributions
  • Random Variables
  • Social Networks
  • Statistics
  • Symmetry

Fields of Study

  • Mathematics

Readers

  • Computer Vision.
  • Software Engineering.
  • Statistical inference.