A Framework for Clustering Longitudinal Data


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Documentation for package ‘latrend’ version 1.1.2

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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
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 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