Codice | 22/2011 |
Titolo | Nonlinear nonparametric mixed-effects models for unsupervised classification |
Data | 2011-05-30 |
Autore/i | Azzimonti, L.; Ieva, F.; Paganoni, A.M. |
Link | Download full text |
Abstract | In this work we propose a novel estimation method for nonlinear nonparametric mixed-effects models, aimed at unsupervised classification. The proposed method is an iterative algorithm that alternates a nonparametric EM step and a nonlinear Maximum Likelihood step. We perform simulation studies in order to evaluate the algorithm performances and we apply this new procedure to a real dataset.
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