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Entropy
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Maximum Entropy 2010
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Maximum Entropy 2010

A special issue of Entropy (ISSN 1099-4300).

Deadline for manuscript submissions: closed (15 December 2010)

Special Issue Editor

Dr. Peter Harremoës

E-Mail Website
Guest Editor
Copenhagen Business College, Rønne Alle 1, st., 2860 Søborg, Denmark
Interests: cause and effect; entropy; exponential families; graphical models; information divergence; minimum description length; quantum information; statistical mechanics
Special Issues, Collections and Topics in MDPI journals

Keywords

  • maximum entropy, Maxent
  • Bayesian inference
  • maximum entropy principle
  • maximum entropy method
  • maximum entropy analysis
  • maximum entropy distribution

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Published Papers (1 paper)

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Research

8 pages, 64 KiB  
Article
A Microeconomic Interpretation of the Maximum Entropy Estimator of Multinomial Logit Models and Its Equivalence to the Maximum Likelihood Estimator
by Pedro Donoso and Louis de Grange
Entropy 2010, 12(10), 2077-2084; https://doi.org/10.3390/e12102077 - 29 Sep 2010
Cited by 13 | Viewed by 7401
Abstract
Maximum entropy models are often used to describe supply and demand behavior in urban transportation and land use systems. However, they have been criticized for not representing behavioral rules of system agents and because their parameters seems to adjust only to modeler-imposed constraints. [...] Read more.
Maximum entropy models are often used to describe supply and demand behavior in urban transportation and land use systems. However, they have been criticized for not representing behavioral rules of system agents and because their parameters seems to adjust only to modeler-imposed constraints. In response, it is demonstrated that the solution to the entropy maximization problem with linear constraints is a multinomial logit model whose parameters solve the likelihood maximization problem of this probabilistic model. But this result neither provides a microeconomic interpretation of the entropy maximization problem nor explains the equivalence of these two optimization problems. This work demonstrates that an analysis of the dual of the entropy maximization problem yields two useful alternative explanations of its solution. The first shows that the maximum entropy estimators of the multinomial logit model parameters reproduce rational user behavior, while the second shows that the likelihood maximization problem for multinomial logit models is the dual of the entropy maximization problem. Full article
(This article belongs to the Special Issue Maximum Entropy 2010)
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