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Parameter Estimation in Nonlinear Mixed Effect Models Using saemix, an R Implementation of the SAEM Algorithm

Abstract : The saemix package for R provides maximum likelihood estimates of parameters in nonlinear mixed effect models, using a modern and efficient estimation algorithm, the stochastic approximation expectation-maximisation (SAEM) algorithm. In the present paper we describe the main features of the package, and apply it to several examples to illustrate its use. Making use of S4 classes and methods to provide user-friendly interaction, this package provides a new estimation tool to the R community.
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https://www.hal.inserm.fr/inserm-01502767
Contributor : Emmanuelle Comets <>
Submitted on : Wednesday, April 12, 2017 - 3:14:41 PM
Last modification on : Wednesday, September 16, 2020 - 5:12:09 PM
Long-term archiving on: : Thursday, July 13, 2017 - 12:18:06 PM

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Emmanuelle Comets, Audrey Lavenu, Marc Lavielle. Parameter Estimation in Nonlinear Mixed Effect Models Using saemix, an R Implementation of the SAEM Algorithm. Journal of Statistical Software, University of California, Los Angeles, 2017, 80 (3), pp.i03. ⟨10.18637/jss.v080.i03⟩. ⟨inserm-01502767⟩

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