Parameter Estimation in Nonlinear Mixed Effect Models Using saemix, an R Implementation of the SAEM Algorithm - Archive ouverte HAL Access content directly
Journal Articles Journal of Statistical Software Year : 2017

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

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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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Dates and versions

inserm-01502767 , version 1 (12-04-2017)

Licence

Public Domain

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