Stochastic Approximation Expectation Maximization (SAEM) Algorithm

Documentation for package ‘saemix’ version 3.3

DESCRIPTION file.

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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 covariates
transformCatCov	Transform covariates
transformContCov	Transform 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