Nonlinear nonparametric mixed-effects models for unsupervised classification

被引：10
|
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.
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页码：1549 / 1570
页数：22
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