2003 Prépublication d'Orsay numéro 2003-20 (07/11/2003)



MAXIMUM LIKELIHOOD ESTIMATION IN NONLINEAR MIXED EFFECTS MODELS.

KUHN, Estelle - Modélisation Stochastique et Statistique, Université Paris-Sud, Bât. 425, 91405 Orsay cedex
LAVIELLE, Marc - Modélisation Stochastique et Statistique, Université Paris-Sud, Bât. 425, 91405 Orsay cedex


Mots Clés : Mixed effects model; Nonlinear models; Maximum likelihood estimation; EM algorithm; SAEM algorithm.

Classification MSC : -


Resumé :

Abstract :
A stochastic approximation version of EM for maximum likelihood estimation of a wide class of nonlinear mixed effects models is proposed. The main advantage of this algorithm is it stability to provide an estimator close to the MLE in very few iterations. The likelihood of the observations as well as the Fisher Information matrix can also be estimated by stochastic approximations. Numerical experiments allow to highlight the very good performances of the proposed method.

Contact : Marc.Lavielle@math.u-psud.fr