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Rearrangement algorithm and maximum entropy

Carole Bernard (), Oleg Bondarenko () and Steven Vanduffel ()
Additional contact information
Carole Bernard: Grenoble Ecole de Management
Oleg Bondarenko: University of Illinois at Chicago
Steven Vanduffel: Vrije Universiteit Brussel (VUB)

Annals of Operations Research, 2018, vol. 261, issue 1, 107-134

Abstract: Abstract We study properties of the block rearrangement algorithm (BRA) in the context of inferring dependence among variables given their marginal distributions and the distribution of their sum. We show that when all distributions are Gaussian the BRA yields solutions that are “close to each other” and exhibit almost maximum entropy, i.e., the inferred dependence is Gaussian with a correlation matrix that has maximum possible determinant. We provide evidence that, when the distributions are no longer Gaussian, the property of maximum determinant continues to hold. The consequences of these findings are that the BRA can be used as a stable algorithm for inferring a dependence that is economically meaningful.

Keywords: Entropy; Block rearrangement algorithm; Inferring dependence (search for similar items in EconPapers)
Date: 2018
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