Electronic Journal of Statistics
- Electron. J. Statist.
- Volume 8, Number 1 (2014), 1661-1695.
Mixture of Gaussian regressions model with logistic weights, a penalized maximum likelihood approach
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.
Electron. J. Statist. Volume 8, Number 1 (2014), 1661-1695.
First available in Project Euclid: 11 September 2014
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Mathematical Reviews number (MathSciNet)
Zentralblatt MATH identifier
Primary: 62G08: Nonparametric regression
Montuelle, L.; Le Pennec, E. Mixture of Gaussian regressions model with logistic weights, a penalized maximum likelihood approach. Electron. J. Statist. 8 (2014), no. 1, 1661--1695. doi:10.1214/14-EJS939. https://projecteuclid.org/euclid.ejs/1410441420