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saemix  

Stochastic Approximation Expectation Maximization (SAEM) Algorithm
View on CRAN: Click here


Download and install saemix package within the R console
Install from CRAN:
install.packages("saemix")

Install from Github:
library("remotes")
install_github("cran/saemix")

Install by package version:
library("remotes")
install_version("saemix", "3.3")



Attach the package and use:
library("saemix")
Maintained by
Emmanuelle Comets
[Scholar Profile | Author Map]
First Published: 2011-06-30
Latest Update: 2023-06-27
Description:
The 'saemix' package implements the Stochastic Approximation EM algorithm for parameter estimation in (non)linear mixed effects models. The SAEM algorithm (i) computes the maximum likelihood estimator of the population parameters, without any approximation of the model (linearisation, quadrature approximation,...), using the Stochastic Approximation Expectation Maximization (SAEM) algorithm, (ii) provides standard errors for the maximum likelihood estimator (iii) estimates the conditional modes, the conditional means and the conditional standard deviations of the individual parameters, using the Hastings-Metropolis algorithm (see Comets et al. (2017) ). Many applications of SAEM in agronomy, animal breeding and PKPD analysis have been published by members of the Monolix group. The full PDF documentation for the package including references about the algorithm and examples can be downloaded on the github of the IAME research institute for 'saemix': .
How to cite:
Emmanuelle Comets (2011). saemix: Stochastic Approximation Expectation Maximization (SAEM) Algorithm. R package version 3.3, https://cran.r-project.org/web/packages/saemix. Accessed 04 May. 2025.
Previous versions and publish date:
0.95 (2011-06-30 19:04), 0.96.1 (2013-03-01 18:11), 0.96 (2011-07-02 14:22), 1.2 (2014-02-25 17:11), 2.1 (2017-08-24 13:55), 2.2 (2018-10-10 18:00), 2.3 (2019-12-06 18:10), 2.4 (2021-02-24 00:00), 3.0 (2022-02-08 16:30), 3.1 (2022-08-05 17:00), 3.2 (2023-06-27 12:10)
Other packages that cited saemix R package
View saemix citation profile
Other R packages that saemix depends, imports, suggests or enhances
Complete documentation for saemix
Functions, R codes and Examples using the saemix R package
Some associated functions: PD1.saemix . SaemixData-class . SaemixModel-class . SaemixObject-class . SaemixRes-class . backward.procedure . boostrap.data . coef.saemix . compare.saemix . conddist.saemix . cow.saemix . createSaemixObject . default.saemix.plots . discreteVPC . discreteVPCTTE . epilepsy.saemix . extract-methods . fim.saemix . fitted.saemix . forward.procedure . initialize-methods . knee.saemix . llgq.saemix . llis.saemix . logLik . lung.saemix . map.saemix . mydiag . npdeSaemix . oxboys.saemix . plot-SaemixData . plot-SaemixModel-SaemixData-method . plot-SaemixModel . plot-SaemixObject-ANY-method . plot-methods . plotDiscreteData . predict-methods . predict.SaemixModel . print-methods . psi-methods . rapi.saemix . read-methods . readSaemix-methods . replaceData . resid.saemix . saemix.bootstrap . saemix.internal . saemix . saemix.plot.data . saemix.plot.select . saemix.plot.setoptions . saemix.predict . saemixControl . saemixData . saemixModel . saemixPredictNewdata . show-methods . showall-methods . simulate.SaemixObject . simulateDiscreteSaemix . step.saemix . stepwise.procedure . sub-SaemixModel-method . sub-SaemixObject-method . sub-SaemixRes-method . subset . summary-methods . testnpde . theo.saemix . toenail.saemix . transform . transformCatCov . transformContCov . validate.covariance.model . validate.names . vcov . xbinning . yield.saemix . 
Some associated R codes: SaemixData.R . SaemixModel.R . SaemixObject.R . SaemixRes.R . aaa_generics.R . backward.R . compute_LL.R . forward.R . func_FIM.R . func_aux.R . func_bootstrap.R . func_compare.R . func_discreteVPC.R . func_distcond.R . func_estimParam.R . func_exploreData.R . func_npde.R . func_plots.R . func_simulations.R . func_stepwise.R . main.R . main_estep.R . main_initialiseMainAlgo.R . main_mstep.R . stepwise.R . zzz.R .  Full saemix package functions and examples
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