[R-pkgs] saemix: SAEM algorithm for parameter estimation in non-linear mixed-effect models (version 0.96)

From: Emmanuelle Comets <emmanuelle.comets_at_inserm.fr>
Date: Mon, 05 Sep 2011 13:02:02 +0200

        saemix implements the SAEM (stochastic approximation EM) algorithm for parameter estimation in non-linear mixed effect models, used to model longitudinal data.

        Longitudinal data are particularly prominent in pharmacokinetics (study of drug concentrations versus time) and pharmacodynamics (study of drug effect versus time), but the SAEM algorithm has also been successfully applied in many other areas and we would like to encourage you to try saemix.

        More details can be found in the user guide included in the package, which encloses a section showing different examples using SAEMIX.

        As always, I would be very grateful for comments and suggestions, and would welcome any feed-back.

                        Emmanuelle Comets

Authors: Emmanuelle Comets, Audrey Lavenu and Marc Lavielle

Statistiquement, tout s'explique.
Personnellement, tout se complique.
         (Daniel Pennac)

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Received on Wed 07 Sep 2011 - 01:19:23 EST

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