# A Framework for Clustering Longitudinal Data

## Documentation for package ‘latrend’ version 1.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

A C D E F G I L M N P Q R S T U V W misc

latrend-package | latrend: A Framework for Clustering Longitudinal Data

## -- A --

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

## -- C --

clusterNames | Get the cluster names
clusterNames<- | Update the cluster names
clusterProportions | Proportional size of each cluster
clusterProportions-method | Proportional size of each cluster
clusterSizes | Number of strata per cluster
clusterTrajectories | Extract the cluster trajectories
clusterTrajectories-method | Extract the cluster trajectories
coef.lcModel | Coefficients of a lcModel
compose | lcMethod class
compose-method | lcMethod class
confusionMatrix | Compute the posterior confusion matrix
converged | Check model convergence
converged-method | 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

## -- D --

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

## -- E --

estimationTime | Get the model estimation time
evaluate.lcMethod | Substitute the call arguments for their evaluated values
externalMetric | Compute external model metric(s)
externalMetric-method | Compute external model metric(s)

## -- F --

fit | lcMethod class
fit-method | lcMethod class
fitted.lcApproxModel | lcApproxModel class
fitted.lcModel | Extract lcModel fitted values
formula.lcMethod | Extract formula
formula.lcModel | Extract the formula of a lcModel

## -- G --

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
getLabel | lcMethod class
getLabel-method | lcMethod class
getLabel-method | lcModel class
getLcMethod | Get the method specification of a lcModel
getName | lcMethod class
getName-method | lcMethod class
getName-method | lcModel class
getShortName | lcMethod class
getShortName-method | lcMethod class
getShortName-method | lcModel class

## -- I --

ids | Get the unique ids included in this model
idVariable | Extract the trajectory identifier variable
idVariable-method | Extract the trajectory identifier variable

## -- L --

latrend | Cluster longitudinal data
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 | lcApproxModel class
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
lcMethodLcmmGBTM | Specify GBTM method
lcMethodLcmmGMM | Specify GMM method using lcmm
lcMethodLMKM | Two-step clustering through linear regression modeling and k-means
lcMethodLongclust | Specify Longclust method
lcMethodMclustLLPA | Longitudinal latent profile analysis
lcMethodMixAK_GLMM | Specify a GLMM iwht a normal mixture in the random effects
lcMethodMixtoolsGMM | Specify mixed mixture regression model using mixtools
lcMethodMixtoolsNPRM | Specify non-parametric estimation for independent repeated measures
lcMethodMixTVEM | Specify a MixTVEM
lcMethodRandom | Specify a random-partitioning method
lcMethods | Generate a list of lcMethod objects
lcMethodStratify | Specify a stratification method
lcModel-class | lcModel class
lcModelCustom | Specify a model based on a pre-computed result.
lcModelPartition | Create a lcModel with pre-defined partitioning
lcModels | Construct a flat (named) list of lcModel objects
lcModelWeightedPartition | Create a lcModel with pre-defined weighted partitioning
length-method | lcMethod class
logLik.lcModel | Extract the log-likelihood of a lcModel

## -- M --

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)
metric-method | 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

## -- N --

names-method | lcMethod class
nClusters | Number of clusters
nIds | Number of strata
nobs.lcModel | Extract the number of observations from a lcModel

## -- P --

plot-method | Plot a lcModel
plotClusterTrajectories | Plot cluster trajectories
plotClusterTrajectories-method | Plot cluster trajectories
plotMetric | Plot one or more internal metrics for all lcModels
plotTrajectories | Plot trajectories
plotTrajectories-method | Plot trajectories
postFit | lcMethod class
postFit-method | lcMethod class
postprob | Posterior probability per fitted id
postprob-method | 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
predictAssignments-method | Predict the cluster assignments for new trajectories
predictForCluster | lcModel prediction for a specific cluster
predictForCluster-method | lcApproxModel class
predictForCluster-method | lcModel prediction for a specific cluster
predictPostprob | lcModel posterior probability prediction
predictPostprob-method | lcModel posterior probability prediction
preFit | lcMethod class
preFit-method | lcMethod class
prepareData | lcMethod class
prepareData-method | lcMethod class
print.lcMethod | Print the arguments of an lcMethod object
print.lcModels | Print lcModels list concisely

## -- Q --

qqPlot | Quantile-quantile plot
qqPlot-method | Quantile-quantile plot

## -- R --

residuals.lcModel | Extract lcModel residuals
responseVariable | Extract the response variable
responseVariable-method | Extract the response variable

## -- S --

sigma.lcModel | Extract residual standard deviation from a lcModel
strip | Strip a lcModel for serialization
strip-method | Strip a lcModel for serialization
subset.lcModels | Subsetting a lcModels list based on method arguments
summary.lcModel | Summarize a lcModel

## -- T --

time.lcModel | Sampling times of a lcModel
timeVariable | Extract the time variable
timeVariable-method | Extract the time variable
trajectories | Extract the fitted trajectories for all strata
trajectories-method | Extract the fitted trajectories for all strata
trajectoryAssignments | Get the cluster membership of each trajectory
trajectoryAssignments-method | Get the cluster membership of each trajectory
transformFitted | Helper function for ensuring the right fitted() output
transformFitted-method | Helper function for ensuring the right fitted() output
transformLatrendData | Transform latrend input data into the right format
transformLatrendData-method | Transform latrend input data into the right format
transformPredict | Helper function that matches the output to the specified newdata
transformPredict-method | Helper function that matches the output to the specified newdata

## -- U --

update.lcMethod | Update a method specification
update.lcModel | Update a lcModel

## -- V --

validate | lcMethod class
validate-method | lcMethod class

## -- W --

which.weight | Sample an index of a vector weighted by the elements

## -- misc --

$-method | Retrieve and evaluate a lcMethod argument by name
[[-method | Retrieve and evaluate a lcMethod argument by name
_PACKAGE | latrend: A Framework for Clustering Longitudinal Data