Package: saemix 3.3

saemix: Stochastic Approximation Expectation Maximization (SAEM) Algorithm

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) <doi:10.18637/jss.v080.i03>). 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': <https://github.com/iame-researchCenter/saemix/blob/7638e1b09ccb01cdff173068e01c266e906f76eb/docsaem.pdf>.

Authors:Emmanuelle Comets [aut, cre], Audrey Lavenu [aut], Marc Lavielle [aut], Belhal Karimi [aut], Maud Delattre [ctb], Marilou Chanel [ctb], Johannes Ranke [ctb], Sofia Kaisaridi [ctb], Lucie Fayette [ctb]

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saemix/json (API)

# Install 'saemix' in R:
install.packages('saemix', repos = c('https://ecomets.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

144 exports 1 stars 3.97 score 31 dependencies 5 dependents 4 mentions 155 scripts 643 downloads

Last updated 7 months agofrom:52eedf08df. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 02 2024
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R-4.5-linuxNOTEOct 02 2024
R-4.4-winOKOct 02 2024
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R-4.3-macOKOct 02 2024

Exports:advanced.gofAIC.SaemixObjectbackward.procedurebasic.gofBIC.covariateBIC.SaemixObjectcenter.epscenter.etacenterDist.NPcondcheckInitialFixedEffectscoef.SaemixObjectcompare.saemixcompute.eta.mapcompute.LLycompute.srescompute.Uyconddist.saemixconditional.distribution_cconditional.distribution_dcovariate.fitscreateSaemixObject.emptycreateSaemixObject.initialcutoffcutoff.epscutoff.maxcutoff.resdataGen.casedataGen.NPdataGen.Pardefault.saemix.plotsderivphidiscreteVPCdiscreteVPC.auxdiscreteVPCcatdiscreteVPCcountdiscreteVPCTTEdtransphierrorerror.typestepestimateIndividualParametersNewdataestimateMeanParametersNewdataetaexploreDataCatexploreDataCountHistexploreDataTTEfim.saemixfitted.SaemixObjectfitted.SaemixResforward.proceduregammarnd.mlxgqg.mlxindividual.fitsinitialiseMainAlgoinitializeinterpol.lininterpol.locfkurtosisllgq.saemixllis.saemixlogLik.SaemixObjectmap.saemixmstepmydiagnormalise.etanormalise.eta.svdnormcdfnorminvnpdeSaemixphiplotplot.SaemixDataplot.SaemixSimDataplotDiscreteDataplotDiscreteData.auxplotDiscreteDataElementplotnpdepredictpredict.SaemixModelprintpsireadSaemixreplace.data.optionsreplace.plot.optionsreplaceData.saemixObjectresid.SaemixObjectresid.SaemixRessaemixsaemix.bootstrapsaemix.data.setoptionssaemix.plot.convergencesaemix.plot.correlationssaemix.plot.datasaemix.plot.distpsisaemix.plot.distribresidualssaemix.plot.fitssaemix.plot.llissaemix.plot.mirrorsaemix.plot.npdesaemix.plot.obsvspredsaemix.plot.parcovsaemix.plot.parcov.auxsaemix.plot.randeffsaemix.plot.randeffcovsaemix.plot.scatterresidualssaemix.plot.selectsaemix.plot.setoptionssaemix.plot.vpcsaemix.predictsaemixControlsaemixDatasaemixModelsaemixPredictNewdatasampDist.NPsampDist.NPcondsampDist.Parshowshowallsimul.saemixsimulate.SaemixObjectsimulateContinuousSaemixsimulateDiscreteSaemixsimulateIndividualParameterssimulateTTESaemixskewnessssqstep.saemixstepwise.proceduresubset.SaemixDatasummarytestnpdetpdf.mlxtransform.numerictransform.SaemixDatatransformCatCovtransformContCovtransphitranspsitrnd.mlxvalidate.covariance.modelvalidate.namesvcov.SaemixObjectvcov.SaemixResxbinning

Dependencies:clicolorspacefansifarverggplot2gluegridExtragtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmclustmgcvmunsellnlmenpdepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr

Readme and manuals

Help Manual

Help pageTopics
Get/set methods for SaemixData object[ [,SaemixData-method [,SaemixRepData-method [,SaemixSimData-method [<-,SaemixData-method [<-,SaemixRepData-method [<-,SaemixRes-method [<-,SaemixSimData-method
Get/set methods for SaemixModel object[,SaemixModel-method
Get/set methods for SaemixObject object[,SaemixObject-method
Get/set methods for SaemixRes object[,SaemixRes-method
Backward procedure for joint selection of covariates and random effectsbackward.procedure
Check initial fixed effects for an SaemixModel object applied to an SaemixData objectcheckInitialFixedEffects
Extract coefficients from an saemix fitcoef coef,SaemixObject coef,SaemixObject-method coef.saemix coef.SaemixObject
Model comparison with information criteria (AIC, BIC).compare.saemix
Estimate conditional mean and variance of individual parameters using the MCMC algorithmconddist.saemix
Evolution of the weight of 560 cows, in SAEM formatcow.saemix
Create saemix objects with only data filled increateSaemixObject createSaemixObject.empty createSaemixObject.initial
Bootstrap datasetsdataGen.case dataGen.NP dataGen.Par sampDist.NP sampDist.NPcond sampDist.Par
Wrapper functions to produce certain sets of default plotsadvanced.gof basic.gof covariate.fits default.saemix.plots individual.fits
VPC for non Gaussian data modelsdiscreteVPC discreteVPC.aux discreteVPCcat discreteVPCcount
VPC for time-to-event modelsdiscreteVPCTTE interpol.lin interpol.locf
Epilepsy count dataepilepsy.saemix
Computes the Fisher Information Matrix by linearisationfim.saemix
Extract Model Predictionsfitted fitted.saemix fitted.SaemixObject fitted.SaemixRes
Backward procedure for joint selection of covariates and random effectsforward.procedure
Methods for Function initializeinitialize,SaemixData-method initialize,SaemixModel-method initialize,SaemixObject-method initialize,SaemixRepData-method initialize,SaemixRes-method initialize,SaemixSimData-method initialize-methods
Knee pain dataknee.saemix
Log-likelihood using Gaussian Quadraturegqg.mlx llgq.saemix llqg.saemix
Log-likelihood using Importance Samplingllis.saemix
Extract likelihood from an SaemixObject resulting from a call to saemixAIC.SaemixObject BIC.covariate BIC.SaemixObject logLik logLik.SaemixObject
NCCTG Lung Cancer Data, in SAEM formatlung.saemix
Estimates of the individual parameters (conditional mode)map.saemix
Matrix diagonalmydiag
Create an npdeObject from an saemixObjectnpdeSaemix
Heights of Boys in Oxfordoxboys.saemix
Data simulated according to an Emax response model, in SAEM formatPD1.saemix PD2.saemix
Methods for Function plotplot,ANY-method plot-methods
Plot model predictions using an SaemixModel objectplot,SaemixModel plot,SaemixModel,ANY-method plot,SaemixModel-methods plot-SaemixModel
Plot model predictions for a new dataset. If the dataset is large, only the first 20 subjects (id's) will be shown.plot,SaemixModel,SaemixData-method plot.SaemixModel
General plot function from SAEMplot plot,SaemixObject plot,SaemixObject,ANY-method plot.saemix plotnpde
Plot of longitudinal dataplot,SaemixData plot,SaemixData,ANY-method plot,SaemixData-methods plot,SaemixSimData plot,SaemixSimData,ANY-method plot,SaemixSimData-method plot-SaemixData plot.SaemixData plot.SaemixSimData
Plot non Gaussian dataexploreDataCat exploreDataCountHist exploreDataTTE plotDiscreteData plotDiscreteData.aux plotDiscreteDataElement
Methods for Function predictpredict,ANY-method predict,SaemixObject-method predict-methods
Predictions for a new datasetpredict.SaemixModel
Methods for Function printprint,ANY-method print,SaemixData-method print,SaemixModel-method print,SaemixObject-method print,SaemixRes-method print-methods print.saemix
Functions to extract the individual estimates of the parameters and random effectseta eta,SaemixObject-method eta-methods eta.saemix eta.SaemixObject phi phi,SaemixObject-method phi-methods phi.saemix phi.SaemixObject psi psi,SaemixObject-method psi-methods psi.saemix psi.SaemixObject
Rutgers Alcohol Problem Indexrapi.saemix
Create a longitudinal data structure from a file or a dataframe Helper function not intended to be called by the userreadSaemix,SaemixData readSaemix,SaemixData-method
Replace the data element in an SaemixObject objectreplaceData replaceData-methods replaceData.saemixObject
Extract Model Residualsresid resid.saemix resid.SaemixObject resid.SaemixRes residuals residuals.saemix residuals.SaemixObject residuals.SaemixRes
Stochastic Approximation Expectation Maximization (SAEM) algorithmestep initialiseMainAlgo mstep saemix
Bootstrap for saemix fitssaemix.bootstrap
Functions implementing each type of plot in SAEMcompute.eta.map compute.sres saemix.plot.convergence saemix.plot.correlations saemix.plot.data saemix.plot.distpsi saemix.plot.distribresiduals saemix.plot.fits saemix.plot.llis saemix.plot.mirror saemix.plot.npde saemix.plot.obsvspred saemix.plot.parcov saemix.plot.parcov.aux saemix.plot.randeff saemix.plot.randeffcov saemix.plot.scatterresiduals saemix.plot.vpc
Plots of the results obtained by SAEMsaemix.plot.select
Function setting the default options for the plots in SAEMreplace.data.options replace.plot.options saemix.data.setoptions saemix.plot.setoptions
Compute model predictions after an saemix fitsaemix.predict
List of options for running the algorithm SAEMsaemixControl
Function to create an SaemixData objectsaemixData
Class "SaemixData"print,SaemixData SaemixData SaemixData-class SaemixRepData SaemixRepData-class SaemixSimData SaemixSimData-class show,SaemixData showall,SaemixData
Function to create an SaemixModel objectsaemixModel
Class "SaemixModel"print,SaemixModel SaemixModel SaemixModel-class show,SaemixModel showall,SaemixModel summary,SaemixModel [<-,SaemixModel-method
Class "SaemixObject"predict,SaemixObject print,SaemixObject SaemixObject SaemixObject-class show,SaemixObject showall,SaemixObject summary,SaemixObject [<-,SaemixObject-method
Predictions for a new datasetestimateIndividualParametersNewdata estimateMeanParametersNewdata saemixPredictNewdata
Class "SaemixRes"plot,SaemixRes print,SaemixRes SaemixRes SaemixRes-class show,SaemixRes showall,SaemixRes
Methods for Function showshow,SaemixData-method show,SaemixModel-method show,SaemixObject-method show,SaemixRepData-method show,SaemixRes-method show,SaemixSimData-method show-methods
Methods for Function showallshowall showall,SaemixData-method showall,SaemixModel-method showall,SaemixObject-method showall,SaemixRes-method showall-methods
Perform simulations under the model for an saemixObject objectsimul.saemix simulate.SaemixObject simulateContinuousSaemix simulateIndividualParameters
Perform simulations under the model for an saemixObject object defined by its log-likelihoodsimulateDiscreteSaemix simulateTTESaemix
Stepwise procedure for joint selection of covariates and random effectsstep.saemix
Stepwise procedure for joint selection of covariates and random effectsstepwise.procedure
Data subsettingsubset subset-methods subset.SaemixData
Methods for Function summarysummary summary,ANY-method summary,SaemixData summary,SaemixData-method summary,SaemixModel-method summary,SaemixObject-method summary,SaemixRes-method summary-methods
Tests for normalised prediction distribution errorskurtosis skewness testnpde
Pharmacokinetics of theophyllinetheo.saemix
Toenail datatoenail.saemix
Transform covariatestransform transform.numeric
Transform covariatestransformCatCov
Transform covariatestransform.SaemixData transformContCov
Validate the structure of the covariance modelvalidate.covariance.model
Name validation (## )Helper function not intended to be called by the user)validate.names
Extracts the Variance-Covariance Matrix for a Fitted Model Objectvcov vcov.SaemixObject vcov.SaemixRes
Internal functions used to produce prediction intervals (from the npde package)xbinning
Wheat yield in crops treated with fertiliser, in SAEM formatyield.saemix