The Data-Constrained Generalized Maximum Entropy Estimator of the GLM: Asymptotic Theory and Inference

The Data-Constrained Generalized Maximum Entropy Estimator of the GLM: Asymptotic Theory and Inference

Maximum entropy methods of parameter estimation are appealing because they impose no additional structure on the data, other than that explicitly assumed by the analyst. In this paper we prove that the data constrained GME estimator of the general linear model is consistent and asymptotically normal...

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Bibliographic Details
Main Authors: Nicholas Scott Cardell, Ron Mittelhammer, Thomas L. Marsh
Format: Article
Language:English
Published: MDPI AG 2013-05-01
Series:Entropy
Subjects:
generalized maximum entropy
generalized maximum cross-entropy
asymptotic Theory
GME computation
unbiased GME
GME as Bayesian estimation
Online Access:http://www.mdpi.com/1099-4300/15/5/1756

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