Nonlinear nonparametric mixed-effects models for unsupervised classification
نویسندگان
چکیده
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.
منابع مشابه
Complex Models and Computational Methods in Statistics 123
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تاریخ انتشار 2011