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

Emmanuelle Comets, Audrey Lavenu and Marc Lavielle

Journal of Statistical Software, 2017, vol. 080, issue i03

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.

Date: 2017-08-29
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Persistent link: https://EconPapers.repec.org/RePEc:jss:jstsof:v:080:i03

DOI: 10.18637/jss.v080.i03

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