A B C D E F G I K L M N O P R S T V X Y misc
advanced.gof | Wrapper functions to produce certain sets of default plots |
AIC.SaemixObject | Extract likelihood from an SaemixObject resulting from a call to saemix |
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 |
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 |
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 |
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 |
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 |
gqg.mlx | Log-likelihood using Gaussian Quadrature |
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 |
knee.saemix | Knee pain data |
kurtosis | Tests for normalised prediction distribution errors |
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 |
map.saemix | Estimates of the individual parameters (conditional mode) |
mstep | Stochastic Approximation Expectation Maximization (SAEM) algorithm |
mydiag | Matrix diagonal |
npdeSaemix | Create an npdeObject from an saemixObject |
oxboys.saemix | Heights of Boys in Oxford |
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 |
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 |
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 |
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 |
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 |
xbinning | Internal functions used to produce prediction intervals (from the npde package) |
yield.saemix | Wheat yield in crops treated with fertiliser, in SAEM format |
[ | 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 |