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arXiv · 1312.6978

Mod\`ele \`a processus latent et algorithme EM pour la r\'egression non lin\'eaire

Faicel Chamroukhi·Allou Samé·Gérard Govaert·Patrice Aknin
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Abstract

A non linear regression approach which consists of a specific regression model incorporating a latent process, allowing various polynomial regression models to be activated preferentially and smoothly, is introduced in this paper. The model parameters are estimated by maximum likelihood performed via a dedicated expecation-maximization (EM) algorithm. An experimental study using simulated and real data sets reveals good performances of the proposed approach.

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Faicel Chamroukhi, Allou Samé, Gérard Govaert, Patrice Aknin. 2013-12-25. Mod\`ele \`a processus latent et algorithme EM pour la r\'egression non lin\'eaire. https://arxiv.org/abs/1312.6978

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