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:
saemix_3.3.tar.gz
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saemix_3.3.tgz(r-4.4-any)saemix_3.3.tgz(r-4.3-any)
saemix_3.3.tar.gz(r-4.5-noble)saemix_3.3.tar.gz(r-4.4-noble)
saemix_3.3.tgz(r-4.4-emscripten)saemix_3.3.tgz(r-4.3-emscripten)
saemix.pdf |saemix.html✨
saemix/json (API)
| # Install 'saemix' in R: |
| install.packages('saemix', repos = c('https://ecomets.r-universe.dev', 'https://cloud.r-project.org')) |
- PD1.saemix - Data simulated according to an Emax response model, in SAEM format
- PD2.saemix - Data simulated according to an Emax response model, in SAEM format
- cow.saemix - Evolution of the weight of 560 cows, in SAEM format
- knee.saemix - Knee pain data
- lung.saemix - NCCTG Lung Cancer Data, in SAEM format
- oxboys.saemix - Heights of Boys in Oxford
- rapi.saemix - Rutgers Alcohol Problem Index
- theo.saemix - Pharmacokinetics of theophylline
- toenail.saemix - Toenail data
- yield.saemix - Wheat yield in crops treated with fertiliser, in SAEM format
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 9 months agofrom:52eedf08df. Checks:OK: 5 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 01 2024 |
| R-4.5-win | NOTE | Nov 01 2024 |
| R-4.5-linux | NOTE | Nov 01 2024 |
| R-4.4-win | OK | Nov 01 2024 |
| R-4.4-mac | OK | Nov 01 2024 |
| R-4.3-win | OK | Nov 01 2024 |
| R-4.3-mac | OK | Nov 01 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 page | Topics |
|---|---|
| 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 effects | backward.procedure |
| Check initial fixed effects for an SaemixModel object applied to an SaemixData object | checkInitialFixedEffects |
| Extract coefficients from an saemix fit | coef 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 algorithm | conddist.saemix |
| Evolution of the weight of 560 cows, in SAEM format | cow.saemix |
| Create saemix objects with only data filled in | createSaemixObject createSaemixObject.empty createSaemixObject.initial |
| Bootstrap datasets | dataGen.case dataGen.NP dataGen.Par sampDist.NP sampDist.NPcond sampDist.Par |
| Wrapper functions to produce certain sets of default plots | advanced.gof basic.gof covariate.fits default.saemix.plots individual.fits |
| VPC for non Gaussian data models | discreteVPC discreteVPC.aux discreteVPCcat discreteVPCcount |
| VPC for time-to-event models | discreteVPCTTE interpol.lin interpol.locf |
| Epilepsy count data | epilepsy.saemix |
| Computes the Fisher Information Matrix by linearisation | fim.saemix |
| Extract Model Predictions | fitted fitted.saemix fitted.SaemixObject fitted.SaemixRes |
| Backward procedure for joint selection of covariates and random effects | forward.procedure |
| Methods for Function initialize | initialize,SaemixData-method initialize,SaemixModel-method initialize,SaemixObject-method initialize,SaemixRepData-method initialize,SaemixRes-method initialize,SaemixSimData-method initialize-methods |
| Knee pain data | knee.saemix |
| Log-likelihood using Gaussian Quadrature | gqg.mlx llgq.saemix llqg.saemix |
| Log-likelihood using Importance Sampling | llis.saemix |
| Extract likelihood from an SaemixObject resulting from a call to saemix | AIC.SaemixObject BIC.covariate BIC.SaemixObject logLik logLik.SaemixObject |
| NCCTG Lung Cancer Data, in SAEM format | lung.saemix |
| Estimates of the individual parameters (conditional mode) | map.saemix |
| Matrix diagonal | mydiag |
| Create an npdeObject from an saemixObject | npdeSaemix |
| Heights of Boys in Oxford | oxboys.saemix |
| Data simulated according to an Emax response model, in SAEM format | PD1.saemix PD2.saemix |
| Methods for Function plot | plot,ANY-method plot-methods |
| Plot model predictions using an SaemixModel object | plot,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 SAEM | plot plot,SaemixObject plot,SaemixObject,ANY-method plot.saemix plotnpde |
| Plot of longitudinal data | plot,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 data | exploreDataCat exploreDataCountHist exploreDataTTE plotDiscreteData plotDiscreteData.aux plotDiscreteDataElement |
| Methods for Function predict | predict,ANY-method predict,SaemixObject-method predict-methods |
| Predictions for a new dataset | predict.SaemixModel |
| Methods for Function print | print,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 effects | eta 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 Index | rapi.saemix |
| Create a longitudinal data structure from a file or a dataframe Helper function not intended to be called by the user | readSaemix,SaemixData readSaemix,SaemixData-method |
| Replace the data element in an SaemixObject object | replaceData replaceData-methods replaceData.saemixObject |
| Extract Model Residuals | resid resid.saemix resid.SaemixObject resid.SaemixRes residuals residuals.saemix residuals.SaemixObject residuals.SaemixRes |
| Stochastic Approximation Expectation Maximization (SAEM) algorithm | estep initialiseMainAlgo mstep saemix |
| Bootstrap for saemix fits | saemix.bootstrap |
| Functions implementing each type of plot in SAEM | compute.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 SAEM | saemix.plot.select |
| Function setting the default options for the plots in SAEM | replace.data.options replace.plot.options saemix.data.setoptions saemix.plot.setoptions |
| Compute model predictions after an saemix fit | saemix.predict |
| List of options for running the algorithm SAEM | saemixControl |
| Function to create an SaemixData object | saemixData |
| Class "SaemixData" | print,SaemixData SaemixData SaemixData-class SaemixRepData SaemixRepData-class SaemixSimData SaemixSimData-class show,SaemixData showall,SaemixData |
| Function to create an SaemixModel object | saemixModel |
| 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 dataset | estimateIndividualParametersNewdata estimateMeanParametersNewdata saemixPredictNewdata |
| Class "SaemixRes" | plot,SaemixRes print,SaemixRes SaemixRes SaemixRes-class show,SaemixRes showall,SaemixRes |
| Methods for Function show | show,SaemixData-method show,SaemixModel-method show,SaemixObject-method show,SaemixRepData-method show,SaemixRes-method show,SaemixSimData-method show-methods |
| Methods for Function showall | showall showall,SaemixData-method showall,SaemixModel-method showall,SaemixObject-method showall,SaemixRes-method showall-methods |
| Perform simulations under the model for an saemixObject object | simul.saemix simulate.SaemixObject simulateContinuousSaemix simulateIndividualParameters |
| Perform simulations under the model for an saemixObject object defined by its log-likelihood | simulateDiscreteSaemix simulateTTESaemix |
| Stepwise procedure for joint selection of covariates and random effects | step.saemix |
| Stepwise procedure for joint selection of covariates and random effects | stepwise.procedure |
| Data subsetting | subset subset-methods subset.SaemixData |
| Methods for Function summary | summary summary,ANY-method summary,SaemixData summary,SaemixData-method summary,SaemixModel-method summary,SaemixObject-method summary,SaemixRes-method summary-methods |
| Tests for normalised prediction distribution errors | kurtosis skewness testnpde |
| Pharmacokinetics of theophylline | theo.saemix |
| Toenail data | toenail.saemix |
| Transform covariates | transform transform.numeric |
| Transform covariates | transformCatCov |
| Transform covariates | transform.SaemixData transformContCov |
| Validate the structure of the covariance model | validate.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 Object | vcov 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 format | yield.saemix |
