Alternative Computational Methods for Estimation in Multinomial Logit Response Models. Revision.

Abstract

Several algorithms have been proposed for the computation of maximum likelihood estimates for contingency tables. Since multinomial logit response models can be treated as special versions of log-linear models, many of these techniques can be used for logit models as well. In this paper we compare, in a qualitative fashion, the relative merits of (1) two variants of Newton's method developed by Fienberg and Stewart; (2) GLIM, as developed by Nelder and Wedderburn; (3) the BMDP program for stepwise logistic regression; and (4) the widely used method of iterative proportional fitting. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1979
Accession Number
ADA089411

Entities

People

  • G. W. Stewart
  • Michael M. Meyer
  • Stephen E. Fienberg

Organizations

  • University of Minnesota

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Behavioral Research
  • Computational Science
  • Computations
  • Convergence
  • Covariance
  • Data Science
  • Maximum Likelihood Estimation
  • Military Research
  • Minnesota
  • Multivariate Analysis
  • New York
  • Numerical Analysis
  • Statistics
  • United States
  • United States Government
  • Universities

Fields of Study

  • Mathematics

Readers

  • Operations Research
  • Regression Analysis.