R: Stochastic Approximation Expectation Maximization (SAEM) Algorithm

# Stochastic Approximation Expectation Maximization (SAEM) Algorithm

## Documentation for package ‘saemix’ version 3.5

- DESCRIPTION file

## Help Pages

A B C D E F G I K L M N O P R S T V X Y misc

## -- A --

advanced.gof | Wrapper functions to produce certain sets of default plots
AIC.SaemixObject | Extract likelihood from an SaemixObject resulting from a call to saemix

## -- B --

backward.procedure | Backward procedure for joint selection of covariates and random effects
basic.gof | Wrapper functions to produce certain sets of default plots
BIC.covariate | Extract likelihood from an SaemixObject resulting from a call to saemix
BIC.SaemixObject | Extract likelihood from an SaemixObject resulting from a call to saemix

## -- C --

checkInitialFixedEffects | Check initial fixed effects for an SaemixModel object applied to an SaemixData object
coef | Extract coefficients from an saemix fit
coef,SaemixObject | Extract coefficients from an saemix fit
coef-method | Extract coefficients from an saemix fit
coef.saemix | Extract coefficients from an saemix fit
coef.SaemixObject | Extract coefficients from an saemix fit
compare.saemix | Model comparison with information criteria (AIC, BIC).
compute.eta.map | Functions implementing each type of plot in SAEM
compute.sres | Functions implementing each type of plot in SAEM
conddist.saemix | Estimate conditional mean and variance of individual parameters using the MCMC algorithm
covariate.fits | Wrapper functions to produce certain sets of default plots
cow.saemix | Evolution of the weight of 560 cows, in SAEM format
createSaemixObject | Create saemix objects with only data filled in
createSaemixObject.empty | Create saemix objects with only data filled in
createSaemixObject.initial | Create saemix objects with only data filled in

## -- D --

dataGen.case | Bootstrap datasets
dataGen.NP | Bootstrap datasets
dataGen.Par | Bootstrap datasets
default.saemix.plots | Wrapper functions to produce certain sets of default plots
discreteVPC | VPC for non Gaussian data models
discreteVPC.aux | VPC for non Gaussian data models
discreteVPCcat | VPC for non Gaussian data models
discreteVPCcount | VPC for non Gaussian data models
discreteVPCTTE | VPC for time-to-event models

## -- E --

epilepsy.saemix | Epilepsy count data
estep | Stochastic Approximation Expectation Maximization (SAEM) algorithm
estimateIndividualParametersNewdata | Predictions for a new dataset
estimateMeanParametersNewdata | Predictions for a new dataset
eta | Functions to extract the individual estimates of the parameters and random effects
eta-method | Functions to extract the individual estimates of the parameters and random effects
eta-methods | Functions to extract the individual estimates of the parameters and random effects
eta.saemix | Functions to extract the individual estimates of the parameters and random effects
eta.SaemixObject | Functions to extract the individual estimates of the parameters and random effects
exploreDataCat | Plot non Gaussian data
exploreDataCountHist | Plot non Gaussian data
exploreDataTTE | Plot non Gaussian data

## -- F --

fim.saemix | Computes the Fisher Information Matrix by linearisation
fitted | Extract Model Predictions
fitted.saemix | Extract Model Predictions
fitted.SaemixObject | Extract Model Predictions
fitted.SaemixRes | Extract Model Predictions
forward.procedure | Backward procedure for joint selection of covariates and random effects

## -- G --

gqg.mlx | Log-likelihood using Gaussian Quadrature

## -- I --

individual.fits | Wrapper functions to produce certain sets of default plots
initialiseMainAlgo | Stochastic Approximation Expectation Maximization (SAEM) algorithm
initialize-method | Methods for Function initialize
initialize-methods | Methods for Function initialize
interpol.lin | VPC for time-to-event models
interpol.locf | VPC for time-to-event models

## -- K --

knee.saemix | Knee pain data
kurtosis | Tests for normalised prediction distribution errors

## -- L --

llgq.saemix | Log-likelihood using Gaussian Quadrature
llis.saemix | Log-likelihood using Importance Sampling
llqg.saemix | Log-likelihood using Gaussian Quadrature
logLik | Extract likelihood from an SaemixObject resulting from a call to saemix
logLik.SaemixObject | Extract likelihood from an SaemixObject resulting from a call to saemix
lung.saemix | NCCTG Lung Cancer Data, in SAEM format

## -- M --

map.saemix | Estimates of the individual parameters (conditional mode)
mstep | Stochastic Approximation Expectation Maximization (SAEM) algorithm
mydiag | Matrix diagonal

## -- N --

npdeSaemix | Create an npdeObject from an saemixObject

## -- O --

oxboys.saemix | Heights of Boys in Oxford

## -- P --

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
phi | Functions to extract the individual estimates of the parameters and random effects
phi-method | Functions to extract the individual estimates of the parameters and random effects
phi-methods | Functions to extract the individual estimates of the parameters and random effects
phi.saemix | Functions to extract the individual estimates of the parameters and random effects
phi.SaemixObject | Functions to extract the individual estimates of the parameters and random effects
plot | General plot function from SAEM
plot,SaemixData | Plot of longitudinal data
plot,SaemixData-methods | Plot of longitudinal data
plot,SaemixModel | Plot model predictions using an SaemixModel object
plot,SaemixModel-methods | Plot model predictions using an SaemixModel object
plot,SaemixObject | General plot function from SAEM
plot,SaemixRes | Class "SaemixRes"
plot,SaemixSimData | Plot of longitudinal data
plot-method | Plot of longitudinal data
plot-method | Plot model predictions for a new dataset. If the dataset is large, only the first 20 subjects (id's) will be shown.
plot-method | Plot model predictions using an SaemixModel object
plot-method | General plot function from SAEM
plot-method | Methods for Function plot
plot-methods | Methods for Function plot
plot-SaemixData | Plot of longitudinal data
plot-SaemixModel | Plot model predictions using an SaemixModel object
plot.saemix | General plot function from SAEM
plot.SaemixData | Plot of longitudinal data
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.SaemixSimData | Plot of longitudinal data
plotDiscreteData | Plot non Gaussian data
plotDiscreteData.aux | Plot non Gaussian data
plotDiscreteDataElement | Plot non Gaussian data
plotnpde | General plot function from SAEM
predict,SaemixObject | Class "SaemixObject"
predict-method | Methods for Function predict
predict-methods | Methods for Function predict
predict.SaemixModel | Predictions for a new dataset
print,SaemixData | Class "SaemixData"
print,SaemixModel | Class "SaemixModel"
print,SaemixObject | Class "SaemixObject"
print,SaemixRes | Class "SaemixRes"
print-method | Methods for Function print
print-methods | Methods for Function print
print.saemix | Methods for Function print
psi | Functions to extract the individual estimates of the parameters and random effects
psi-method | Functions to extract the individual estimates of the parameters and random effects
psi-methods | Functions to extract the individual estimates of the parameters and random effects
psi.saemix | Functions to extract the individual estimates of the parameters and random effects
psi.SaemixObject | Functions to extract the individual estimates of the parameters and random effects

## -- R --

rapi.saemix | Rutgers Alcohol Problem Index
readSaemix,SaemixData | Create a longitudinal data structure from a file or a dataframe Helper function not intended to be called by the user
readSaemix-method | Create a longitudinal data structure from a file or a dataframe Helper function not intended to be called by the user
replace.data.options | Function setting the default options for the plots in SAEM
replace.plot.options | Function setting the default options for the plots in SAEM
replaceData | Replace the data element in an SaemixObject object
replaceData-methods | Replace the data element in an SaemixObject object
replaceData.saemixObject | Replace the data element in an SaemixObject object
resid | Extract Model Residuals
resid.saemix | Extract Model Residuals
resid.SaemixObject | Extract Model Residuals
resid.SaemixRes | Extract Model Residuals
residuals | Extract Model Residuals
residuals.saemix | Extract Model Residuals
residuals.SaemixObject | Extract Model Residuals
residuals.SaemixRes | Extract Model Residuals

## -- S --

saemix | Stochastic Approximation Expectation Maximization (SAEM) algorithm
saemix.bootstrap | Bootstrap for saemix fits
saemix.data.setoptions | Function setting the default options for the plots in SAEM
saemix.plot.convergence | Functions implementing each type of plot in SAEM
saemix.plot.correlations | Functions implementing each type of plot in SAEM
saemix.plot.data | Functions implementing each type of plot in SAEM
saemix.plot.distpsi | Functions implementing each type of plot in SAEM
saemix.plot.distribresiduals | Functions implementing each type of plot in SAEM
saemix.plot.fits | Functions implementing each type of plot in SAEM
saemix.plot.llis | Functions implementing each type of plot in SAEM
saemix.plot.mirror | Functions implementing each type of plot in SAEM
saemix.plot.npde | Functions implementing each type of plot in SAEM
saemix.plot.obsvspred | Functions implementing each type of plot in SAEM
saemix.plot.parcov | Functions implementing each type of plot in SAEM
saemix.plot.parcov.aux | Functions implementing each type of plot in SAEM
saemix.plot.randeff | Functions implementing each type of plot in SAEM
saemix.plot.randeffcov | Functions implementing each type of plot in SAEM
saemix.plot.scatterresiduals | Functions implementing each type of plot in SAEM
saemix.plot.select | Plots of the results obtained by SAEM
saemix.plot.setoptions | Function setting the default options for the plots in SAEM
saemix.plot.vpc | Functions implementing each type of plot in SAEM
saemix.predict | Compute model predictions after an saemix fit
saemixControl | List of options for running the algorithm SAEM
SaemixData | Class "SaemixData"
saemixData | Function to create an SaemixData object
SaemixData-class | Class "SaemixData"
SaemixModel | Class "SaemixModel"
saemixModel | Function to create an SaemixModel object
SaemixModel-class | Class "SaemixModel"
SaemixObject | Class "SaemixObject"
SaemixObject-class | Class "SaemixObject"
saemixPredictNewdata | Predictions for a new dataset
SaemixRepData | Class "SaemixData"
SaemixRepData-class | Class "SaemixData"
SaemixRes | Class "SaemixRes"
SaemixRes-class | Class "SaemixRes"
SaemixSimData | Class "SaemixData"
SaemixSimData-class | Class "SaemixData"
sampDist.NP | Bootstrap datasets
sampDist.NPcond | Bootstrap datasets
sampDist.Par | Bootstrap datasets
show,SaemixData | Class "SaemixData"
show,SaemixModel | Class "SaemixModel"
show,SaemixObject | Class "SaemixObject"
show,SaemixRes | Class "SaemixRes"
show-method | Methods for Function show
show-methods | Methods for Function show
showall | Methods for Function showall
showall,SaemixData | Class "SaemixData"
showall,SaemixModel | Class "SaemixModel"
showall,SaemixObject | Class "SaemixObject"
showall,SaemixRes | Class "SaemixRes"
showall-method | Methods for Function showall
showall-methods | Methods for Function showall
simul.saemix | Perform simulations under the model for an saemixObject object
simulate.SaemixObject | Perform simulations under the model for an saemixObject object
simulateContinuousSaemix | Perform simulations under the model for an saemixObject object
simulateDiscreteSaemix | Perform simulations under the model for an saemixObject object defined by its log-likelihood
simulateIndividualParameters | Perform simulations under the model for an saemixObject object
simulateTTESaemix | Perform simulations under the model for an saemixObject object defined by its log-likelihood
skewness | Tests for normalised prediction distribution errors
step.saemix | Stepwise procedure for joint selection of covariates and random effects
stepwise.procedure | Stepwise procedure for joint selection of covariates and random effects
subset | Data subsetting
subset-methods | Data subsetting
subset.SaemixData | Data subsetting
summary | Methods for Function summary
summary,SaemixData | Methods for Function summary
summary,SaemixModel | Class "SaemixModel"
summary,SaemixObject | Class "SaemixObject"
summary-method | Methods for Function summary
summary-methods | Methods for Function summary

## -- T --

testnpde | Tests for normalised prediction distribution errors
theo.saemix | Pharmacokinetics of theophylline
toenail.saemix | Toenail data
transform | Transform covariates
transform.numeric | Transform covariates
transform.SaemixData | Transform continuous covariates
transformCatCov | Transform categorical covariates
transformContCov | Transform continuous covariates

## -- V --

validate.covariance.model | Validate the structure of the covariance model
validate.names | Name validation (## )Helper function not intended to be called by the user)
vcov | Extracts the Variance-Covariance Matrix for a Fitted Model Object
vcov.SaemixObject | Extracts the Variance-Covariance Matrix for a Fitted Model Object
vcov.SaemixRes | Extracts the Variance-Covariance Matrix for a Fitted Model Object

## -- X --

xbinning | Internal functions used to produce prediction intervals (from the npde package)

## -- Y --

yield.saemix | Wheat yield in crops treated with fertiliser, in SAEM format

## -- misc --

[ | Get/set methods for SaemixData object
[-method | Get/set methods for SaemixData object
[-method | Get/set methods for SaemixModel object
[-method | Get/set methods for SaemixObject object
[-method | Get/set methods for SaemixRes object
[<--method | Class "SaemixModel"
[<--method | Class "SaemixObject"
[<--method | Get/set methods for SaemixData object