Parameter Estimation in Nonlinear Mixed Effect Models Using saemix , an R Implementation of the SAEM Algorithm
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,...
Gespeichert in:
Veröffentlicht in: | Journal of statistical software 2017, Vol.80 (3), p.1-41 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | 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. |
---|---|
ISSN: | 1548-7660 1548-7660 |
DOI: | 10.18637/jss.v080.i03 |