An improved SAEM algorithm for maximum likelihood estimation in mixtures of non linear mixed effects models

DOI10.1007/s11222-013-9396-2zbMath1322.62171OpenAlexW2082016503MaRDI QIDQ746314

Marc Lavielle, Cyprien Mbogning

Publication date: 16 October 2015

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-013-9396-2

zbMATH Keywords

maximum likelihood estimationSAEM algorithmmixture modelsnonlinear mixed effects model

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Point estimation (62F10) General nonlinear regression (62J02)

Related Items (2)

A mixed stochastic approximation EM (MSAEM) algorithm for the estimation of the four-parameter normal ogive model ⋮ Heavy-tailed longitudinal regression models for censored data: a robust parametric approach

Uses Software

• Monolix

Cites Work

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• Model-Based Gaussian and Non-Gaussian Clustering
• Practical Bayesian Density Estimation Using Mixtures of Normals
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