Package: saemix
Type: Package
Title: Stochastic Approximation Expectation Maximization (SAEM)
        algorithm
Version: 0.96
Date: 2011-04-07
Author: Emmanuelle Comets, Audrey Lavenu, Marc Lavielle.
Maintainer: Emmanuelle Comets <emmanuelle.comets@inserm.fr>
Description: The SAEM 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 (linearization, 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://software.monolix.org/).
License: GPL (>= 2)
LazyLoad: yes
LazyData: yes
Depends: methods
Imports: graphics, stats
Collate: global.R SaemixData.R SaemixModel.R SaemixRes.R SaemixObject.R
        main.R zzz.R
Packaged: 2011-07-01 14:36:58 UTC; eco
Repository: CRAN
Date/Publication: 2011-07-02 14:22:26
