Generalizing the Iterative Proportional Fitting Procedure.

Abstract

The Iterative Proportional Fitting Procedure (IPFP) can be viewed as a method for maximizing the likelihood for certain loglinear models or equivalently for minimizing the Kullback-Leibler Information between two probability densities. Both of these viewpoints lead to natural generalizations of the classical IPFP. We examine the generalizations and, with the aid of the theory, explore a practical example of expanding a contingency table.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1980
Accession Number
ADA084429

Entities

People

  • Michael M. Meyer

Organizations

  • University of Minnesota

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Cell Count
  • Computations
  • Computer Programs
  • Convex Sets
  • Equations
  • Estimators
  • Hilbert Space
  • Iterations
  • Maximum Likelihood Estimation
  • Numbers
  • Observation
  • Probability
  • Probability Distributions
  • Square Roots
  • Statistics
  • Theorems

Fields of Study

  • Mathematics

Readers

  • Regression Analysis.
  • Theoretical Analysis.