Man pages for latrend
A Framework for Clustering Longitudinal Data lcMethod arguments to a list of atomic types a list of lcMethod objects to a data.frame a data.frame containing the argument values per...
as.lcMethodsConvert a list of lcMethod objects to a lcMethods list
as.lcModelsConvert a list of lcModels to a lcModels list
as.list.lcMethodExtract the method arguments as a list
assertlatrend-specific assertions
cashRetrieve and evaluate a lcMethod argument by name
clusterNamesGet the cluster names
clusterNames-setUpdate the cluster names
clusterProportionsProportional size of each cluster
clusterSizesNumber of strata per cluster
clusterTrajectoriesExtract the cluster trajectories
coef.lcModelCoefficients of a lcModel
confusionMatrixCompute the posterior confusion matrix
convergedCheck model convergence
createTestDataFoldCreate the test fold data for validation
createTestDataFoldsCreate all k test folds from the training data
createTrainDataFoldsCreate the training data for each of the k models in k-fold...
dcastRepeatedMeasuresCast a longitudinal data.frame to a matrix
defineExternalMetricDefine an external metric for lcModels
defineInternalMetricDefine an internal metric for lcModels
deviance.lcModellcModel deviance
df.residual.lcModelExtract the residual degrees of freedom from a lcModel
estimationTimeGet the model estimation time
evaluate.lcMethodSubstitute the call arguments for their evaluated values
externalMetricCompute external model metric(s)
fitted.lcModelExtract lcModel fitted values
formula.lcMethodExtract formula
formula.lcModelExtract the formula of a lcModel
generateLongDataGenerate longitudinal test data
getCall.lcModelGet the model call
getExternalMetricDefinitionGet the external metric definition
getExternalMetricNamesGet the names of the available external metrics
getInternalMetricDefinitionGet the internal metric definition
getInternalMetricNamesGet the names of the available internal metrics
getLcMethodGet the method specification of a lcModel
idsGet the unique ids included in this model
idVariableExtract the trajectory identifier variable
indexyRetrieve and evaluate a lcMethod argument by name
interface-akmedoidsakmedoids interface
interface-crimCVcrimCV interface
interface-customcustom interface
interface-dtwclustdtwclust interface
interface-featureBasedfeatureBased interface
interface-flexmixflexmix interface
interface-funFEMfunFEM interface
interface-kmlkml interface
interface-lcmmlcmm interface
interface-longclustlongclust interface
interface-mclustmclust interface
interface-mixAKmixAK interface
interface-mixtoolsmixtools interface
interface-mixtvemmixtvem interface
isCheck if object is of Class
isArgDefinedCheck whether the argument of a lcMethod has a defined value.
latrendCluster longitudinal data
latrendBatchCluster longitudinal data for a list of model specifications
latrendBootCluster longitudinal data using bootstrapping
latrendCVCluster longitudinal data over k folds
latrendDataSynthetic longitudinal dataset comprising three classes
latrend-genericsMethod- and model-specific generics defined by the latrend...
latrend-packagelatrend: A Framework for Clustering Longitudinal Data
latrend-parallelParallel computing using latrend
latrendRepCluster longitudinal data repeatedly
lcApproxModel-classlcApproxModel class
lcMethodCreate a lcMethod object of the specified type and arguments
lcMethodAkmedoidsSpecify AKMedoids method
lcMethod.callCreate a lcMethod object from a call
lcMethod-classlcMethod class
lcMethodCrimCVSpecify a zero-inflated repeated-measures GBTM method
lcMethodCustomSpecify a custom method based on a model function
lcMethodDtwclustSpecify time series clustering via dtwclust
lcMethodFeatureFeature-based clustering
lcMethodFlexmixMethod interface to flexmix()
lcMethodFlexmixGBTMGroup-based trajectory modeling using flexmix
lcMethodFunFEMSpecify a FunFEM method
lcMethodGCKMTwo-step clustering through linear mixed modeling and k-means
lcMethodKMLSpecify a longitudinal k-means (KML) method
lcMethodLcmmGBTMSpecify GBTM method
lcMethodLcmmGMMSpecify GMM method using lcmm
lcMethodLMKMTwo-step clustering through linear regression modeling and...
lcMethodLongclustSpecify Longclust method
lcMethodMclustLLPALongitudinal latent profile analysis
lcMethodMixAK_GLMMSpecify a GLMM iwht a normal mixture in the random effects
lcMethodMixtoolsGMMSpecify mixed mixture regression model using mixtools
lcMethodMixtoolsNPRMSpecify non-parametric estimation for independent repeated...
lcMethodMixTVEMSpecify a MixTVEM
lcMethodRandomSpecify a random-partitioning method
lcMethodsGenerate a list of lcMethod objects
lcMethodStratifySpecify a stratification method
lcModel-classlcModel class
lcModelCustomSpecify a model based on a pre-computed result.
lcModel-data-filtersData filters for lcModel
lcModel-makeCluster-handling functions for lcModel implementations.
lcModelPartitionCreate a lcModel with pre-defined partitioning
lcModelsConstruct a flat (named) list of lcModel objects
lcModelWeightedPartitionCreate a lcModel with pre-defined weighted partitioning
logLik.lcModelExtract the log-likelihood of a lcModel matching with defaults and parent ellipsis expansion
max.lcModelsSelect the lcModel with the highest metric value
meltRepeatedMeasuresConvert a repeated measures data matrix to a data.frame
metricCompute internal model metric(s)
min.lcModelsSelect the lcModel with the lowest metric value
model.dataExtract the model training data the model data that was used for fitting
model.frame.lcModelExtract model training data
nClustersNumber of clusters
nIdsNumber of strata
nobs.lcModelExtract the number of observations from a lcModel
plotClusterTrajectoriesPlot cluster trajectories
plot-lcModel-ANY-methodPlot a lcModel
plotMetricPlot one or more internal metrics for all lcModels
plotTrajectoriesPlot trajectories
postprobPosterior probability per fitted id
postprobFromAssignmentsCreate a posterior probability matrix from a vector of...
postProbFromObsCompute the id-specific postprob matrix from a given...
predictAssignmentsPredict the cluster assignments for new trajectories
predictForClusterlcModel prediction for a specific cluster
predict.lcModellcModel predictions
predictPostproblcModel posterior probability prediction
print.lcMethodPrint the arguments of an lcMethod object
print.lcModelsPrint lcModels list concisely
qqPlotQuantile-quantile plot
residuals.lcModelExtract lcModel residuals
responseVariableExtract the response variable
sigma.lcModelExtract residual standard deviation from a lcModel
stripStrip a lcModel for serialization
subset.lcModelsSubsetting a lcModels list based on method arguments
summary.lcModelSummarize a lcModel
time.lcModelSampling times of a lcModel
timeVariableExtract the time variable
trajectoriesExtract the fitted trajectories for all strata
trajectoryAssignmentsGet the cluster membership of each trajectory
transformFittedHelper function for ensuring the right fitted() output
transformLatrendDataTransform latrend input data into the right format
transformPredictHelper function that matches the output to the specified...
update.lcMethodUpdate a method specification
update.lcModelUpdate a lcModel
weighted.meanNAWeighted arithmetic mean ignoring NAs
which.weightSample an index of a vector weighted by the elements
latrend documentation built on April 14, 2021, 5:08 p.m.