Nonlinear nonparametric mixed-effects models for unsupervised classification

被引：9

作者：

Azzimonti, Laura ^{[1
]}

Ieva, Francesca ^{[1
]}

Paganoni, Anna Maria ^{[1
]}

机构：

[1] Politecn Milan, Dipartimento Matemat, MOX, I-20133 Milan, Italy

来源：

COMPUTATIONAL STATISTICS | 2013年 / 28卷 / 04期

关键词：

Mixed-effects models; Nonparametric estimation; EM algorithm; Nonlinear models; MAXIMUM-LIKELIHOOD ANALYSIS; GENERALIZED LINEAR-MODELS; MIXTURE LIKELIHOODS; EM ALGORITHM; GEOMETRY;

D O I：

10.1007/s00180-012-0366-5

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this work we propose a novel EM method for the estimation of nonlinear nonparametric mixed-effects models, aimed at unsupervised classification. We perform simulation studies in order to evaluate the algorithm performance and we apply this new procedure to a real dataset.

引用

页码：1549 / 1570

页数：22

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