Mixture of Gaussian regressions model with logistic weights, a penalized maximum likelihood approach Article - Septembre 2014

Lucie Montuelle, Erwan Le Pennec

Lucie Montuelle, Erwan Le Pennec, « Mixture of Gaussian regressions model with logistic weights, a penalized maximum likelihood approach  », Electronic journal of statistics, septembre 2014, p. 35. ISSN 1935-7524

Abstract

In the framework of conditional density estimation, we use candidates taking the form of mixtures of Gaussian regressions with logistic weights and means depending on the covariate. We aim at estimating the number of components of this mixture, as well as the other parameters, by a penalized maximum likelihood approach. We provide a lower bound on the penalty that ensures an oracle inequality for our estimator. We perform some numerical experiments that support our theoretical analysis.

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