Package: saemix
Type: Package
Title: Stochastic Approximation Expectation Maximization (SAEM)
        algorithm
Version: 1.2
Date: 2014-02-25
Author: Emmanuelle Comets, Audrey Lavenu, Marc Lavielle.
Maintainer: Emmanuelle Comets <emmanuelle.comets@inserm.fr>
Description: 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/).
License: GPL (>= 2)
LazyLoad: yes
LazyData: yes
Imports: graphics, stats, methods
Collate: global.R SaemixData.R SaemixModel.R SaemixRes.R SaemixObject.R
        main.R zzz.R
Packaged: 2014-02-25 15:52:45 UTC; eco
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-02-25 17:11:12
Built: R 3.2.5; ; 2016-11-02 14:11:42 UTC; windows
