$,lcMethod-method       Retrieve and evaluate a lcMethod argument by
                        name
[[,lcMethod-method      Retrieve and evaluate a lcMethod argument by
                        name
as.data.frame.lcMethod
                        Convert lcMethod arguments to a list of atomic
                        types
as.data.frame.lcMethods
                        Convert a list of lcMethod objects to a
                        data.frame
as.data.frame.lcModels
                        Generate a data.frame containing the argument
                        values per method per row
as.lcMethods            Convert a list of lcMethod objects to a
                        lcMethods list
as.lcModels             Convert a list of lcModels to a lcModels list
as.list.lcMethod        Extract the method arguments as a list
clusterNames            Get the cluster names
clusterNames<-          Update the cluster names
clusterProportions      Proportional size of each cluster
clusterSizes            Number of strata per cluster
clusterTrajectories     Extract the cluster trajectories
coef.lcModel            Coefficients of a lcModel
confusionMatrix         Compute the posterior confusion matrix
converged               Check model convergence
createTestDataFold      Create the test fold data for validation
createTestDataFolds     Create all k test folds from the training data
createTrainDataFolds    Create the training data for each of the k
                        models in k-fold cross validation evaluation
dcastRepeatedMeasures   Cast a longitudinal data.frame to a matrix
defineExternalMetric    Define an external metric for lcModels
defineInternalMetric    Define an internal metric for lcModels
deviance.lcModel        lcModel deviance
df.residual.lcModel     Extract the residual degrees of freedom from a
                        lcModel
estimationTime          Get the model estimation time
evaluate.lcMethod       Substitute the call arguments for their
                        evaluated values
externalMetric,lcModel,lcModel-method
                        Compute external model metric(s)
fitted.lcModel          Extract lcModel fitted values
formula.lcMethod        Extract formula
formula.lcModel         Extract the formula of a lcModel
generateLongData        Generate longitudinal test data
getExternalMetricDefinition
                        Get the external metric definition
getExternalMetricNames
                        Get the names of the available external metrics
getInternalMetricDefinition
                        Get the internal metric definition
getInternalMetricNames
                        Get the names of the available internal metrics
getLcMethod             Get the method specification of a lcModel
idVariable              Extract the trajectory identifier variable
ids                     Get the unique ids included in this model
latrend                 Cluster longitudinal data
latrend-package         latrend: A Framework for Clustering
                        Longitudinal Data
latrend-parallel        Parallel computing using latrend
latrendBatch            Cluster longitudinal data for a list of model
                        specifications
latrendBoot             Cluster longitudinal data using bootstrapping
latrendCV               Cluster longitudinal data over k folds
latrendData             Synthetic longitudinal dataset comprising three
                        classes
latrendRep              Cluster longitudinal data repeatedly
lcApproxModel-class     lcApproxModel class
lcMethod                Create a lcMethod object of the specified type
                        and arguments
lcMethod-class          lcMethod class
lcMethod.call           Create a lcMethod object from a call
lcMethodAkmedoids       Specify AKMedoids method
lcMethodCrimCV          Specify a zero-inflated repeated-measures GBTM
                        method
lcMethodCustom          Specify a custom method based on a model
                        function
lcMethodDtwclust        Specify time series clustering via dtwclust
lcMethodFeature         Feature-based clustering
lcMethodFlexmix         Method interface to flexmix()
lcMethodFlexmixGBTM     Group-based trajectory modeling using flexmix
lcMethodFunFEM          Specify a FunFEM method
lcMethodGCKM            Two-step clustering through linear mixed
                        modeling and k-means
lcMethodKML             Specify a longitudinal k-means (KML) method
lcMethodLMKM            Two-step clustering through linear regression
                        modeling and k-means
lcMethodLcmmGBTM        Specify GBTM method
lcMethodLcmmGMM         Specify GMM method using lcmm
lcMethodLongclust       Specify Longclust method
lcMethodMclustLLPA      Longitudinal latent profile analysis
lcMethodMixAK_GLMM      Specify a GLMM iwht a normal mixture in the
                        random effects
lcMethodMixTVEM         Specify a MixTVEM
lcMethodMixtoolsGMM     Specify mixed mixture regression model using
                        mixtools
lcMethodMixtoolsNPRM    Specify non-parametric estimation for
                        independent repeated measures
lcMethodRandom          Specify a random-partitioning method
lcMethodStratify        Specify a stratification method
lcMethods               Generate a list of lcMethod objects
lcModel-class           lcModel class
lcModelCustom           Specify a model based on a pre-computed result.
lcModelPartition        Create a lcModel with pre-defined partitioning
lcModelWeightedPartition
                        Create a lcModel with pre-defined weighted
                        partitioning
lcModels                Construct a flat (named) list of lcModel
                        objects
logLik.lcModel          Extract the log-likelihood of a lcModel
max.lcModels            Select the lcModel with the highest metric
                        value
meltRepeatedMeasures    Convert a repeated measures data matrix to a
                        data.frame
metric                  Compute internal model metric(s)
min.lcModels            Select the lcModel with the lowest metric value
model.data.lcModel      Extract the model data that was used for
                        fitting
model.frame.lcModel     Extract model training data
nClusters               Number of clusters
nIds                    Number of strata
nobs.lcModel            Extract the number of observations from a
                        lcModel
plot,lcModel,ANY-method
                        Plot a lcModel
plotClusterTrajectories
                        Plot cluster trajectories
plotMetric              Plot one or more internal metrics for all
                        lcModels
plotTrajectories        Plot trajectories
postprob                Posterior probability per fitted id
postprobFromAssignments
                        Create a posterior probability matrix from a
                        vector of cluster assignments.
predict.lcModel         lcModel predictions
predictAssignments      Predict the cluster assignments for new
                        trajectories
predictForCluster       lcModel prediction for a specific cluster
predictPostprob         lcModel posterior probability prediction
print.lcMethod          Print the arguments of an lcMethod object
print.lcModels          Print lcModels list concisely
qqPlot                  Quantile-quantile plot
residuals.lcModel       Extract lcModel residuals
responseVariable        Extract the response variable
sigma.lcModel           Extract residual standard deviation from a
                        lcModel
strip                   Strip a lcModel for serialization
subset.lcModels         Subsetting a lcModels list based on method
                        arguments
summary.lcModel         Summarize a lcModel
time.lcModel            Sampling times of a lcModel
timeVariable            Extract the time variable
trajectories            Extract the fitted trajectories for all strata
trajectoryAssignments   Get the cluster membership of each trajectory
transformFitted         Helper function for ensuring the right fitted()
                        output
transformLatrendData    Transform latrend input data into the right
                        format
transformPredict        Helper function that matches the output to the
                        specified newdata
update.lcMethod         Update a method specification
update.lcModel          Update a lcModel
which.weight            Sample an index of a vector weighted by the
                        elements
