Generalized maximum entropy estimation of linear models

Paul Corral Rodas, Daniel Kuehn () and Ermengarde Jabir
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Daniel Kuehn: Urban Institute
Ermengarde Jabir: American University

Stata Journal, 2017, vol. 17, issue 1, 240-249

Abstract: In this article, we describe the user-written gmentropylinear command, which implements the generalized maximum entropy estimation method for linear models. This is an information-theoretic procedure preferable to its maximum likelihood counterparts in many applications; it avoids making distributional assumptions, works well when the sample is small or covariates are highly correlated, and is more efficient than its maximum likelihood equivalent. We give a brief introduction to the generalized maximum entropy procedure, present the gmentropylinear command, and give an example using the command.

Keywords: gmentropylinear; generalized maximum entropy; maximum entropy; linear (search for similar items in EconPapers)
Date: 2017
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