Open Access
March 2010 Density estimation by dual ascent of the log-likelihood
Esteban G. Tabak, Eric Vanden-Eijnden
Commun. Math. Sci. 8(1): 217-233 (March 2010).


A methodology is developed to assign, from an observed sample, a joint-probability distribution to a set of continuous variables. The algorithm proposed performs this assignment by mapping the original variables onto a jointly-Gaussian set. The map is built iteratively, ascending the log-likelihood of the observations, through a series of steps that move the marginal distributions along a random set of orthogonal directions towards normality.


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Esteban G. Tabak. Eric Vanden-Eijnden. "Density estimation by dual ascent of the log-likelihood." Commun. Math. Sci. 8 (1) 217 - 233, March 2010.


Published: March 2010
First available in Project Euclid: 23 February 2010

zbMATH: 1189.62063
MathSciNet: MR2655907

Primary: 34A50 , 60H35 , 65C30 , 65L20

Keywords: Density estimation , machine learning , maximum likelihood

Rights: Copyright © 2010 International Press of Boston

Vol.8 • No. 1 • March 2010
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