The SAEMIX package implements the Stochastic Approximation EM algorithm for parameter estimation in (non)linear mixed effects models. The SAEM algorithm: - computes the maximum likelihood estimator of the population parameters, without any approximation of the model (linearisation, quadrature approximation,...), using the Stochastic Approximation Expectation Maximization (SAEM) algorithm, - provides standard errors for the maximum likelihood estimator - estimates the conditional modes, the conditional means and the conditional standard deviations of the individual parameters, using the Hastings-Metropolis algorithm. Several applications of SAEM in agronomy, animal breeding and PKPD analysis have been published by members of the Monolix group (http://group.monolix.org/).
|Author||Emmanuelle Comets, Audrey Lavenu, Marc Lavielle.|
|Date of publication||2014-02-25 17:11:12|
|Maintainer||Emmanuelle Comets <firstname.lastname@example.org>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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