APPA | Average posterior probability of assignment (APPA) |
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... |
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 |
assert | latrend-specific assertions |
clusterNames | Get the cluster names |
clusterNames-set | Update the cluster names |
clusterProportions | Proportional size of each cluster |
clusterSizes | Number of trajectories per cluster |
clusterTrajectories | Extract cluster trajectories |
coef.lcModel | Extract lcModel coefficients |
compose | 'lcMethod' estimation step: compose an lcMethod object |
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... |
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 |
dot-defineInternalDistanceMetrics | Define the distance metrics for multiple types at once |
dot-guessResponseVariable | Guess the response variable |
dot-trajSubset | Select trajectories |
estimationTime | Estimation time |
evaluate.lcMethod | Substitute the call arguments for their evaluated values |
externalMetric | Compute external model metric(s) |
fit | 'lcMethod' estimation step: logic for fitting the method to... |
fitted.lcModel | Extract lcModel fitted values |
fittedTrajectories | Extract the fitted trajectories |
formula.lcMethod | Extract formula |
formula.lcModel | Extract the formula of a lcModel |
generateLongData | Generate longitudinal test data |
getArgumentDefaults | Default argument values for the given method specification |
getArgumentExclusions | Arguments to be excluded from the specification |
getCall.lcModel | Get the model call |
getCitation | Get citation info |
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 | Object label |
getLcMethod | Get the method specification |
getName | Object name |
ids | Get the trajectory ids on which the model was fitted |
idVariable | Extract the trajectory identifier variable |
indexy | Retrieve and evaluate a lcMethod argument by name |
initialize-lcMethod-method | lcMethod initialization |
interface-akmedoids | akmedoids interface |
interface-crimCV | crimCV interface |
interface-custom | function interface |
interface-dtwclust | dtwclust interface |
interface-featureBased | featureBased interface |
interface-flexmix | flexmix interface |
interface-funFEM | funFEM interface |
interface-kml | kml interface |
interface-lcmm | lcmm interface |
interface-mclust | mclust interface |
interface-metaMethods | lcMetaMethod abstract class |
interface-mixAK | mixAK interface |
interface-mixtools | mixtools interface |
interface-mixtvem | mixtvem interface |
is | Check if object is of Class |
isArgDefined | Check whether the argument of a lcMethod has a defined value. |
latrend | Cluster longitudinal data using the specified method |
latrend-approaches | High-level approaches to longitudinal clustering |
latrendBatch | Cluster longitudinal data for a list of method specifications |
latrendBoot | Cluster longitudinal data using bootstrapping |
latrendCV | Cluster longitudinal data over k folds |
latrend-data | Longitudinal dataset representation |
latrendData | Artificial longitudinal dataset comprising three classes |
latrend-estimation | Overview of *'lcMethod'* estimation functions |
latrend-generics | Generics used by latrend for different classes |
latrend-methods | Supported methods for longitudinal clustering |
latrend-metrics | Metrics |
latrend-package | latrend: A Framework for Clustering Longitudinal Data |
latrend-parallel | Parallel computation using latrend |
latrendRep | Cluster longitudinal data repeatedly |
lcApproxModel-class | lcApproxModel class |
lcFitMethods | Method fit modifiers |
lcMatrixMethod-class | lcMatrixMethod |
lcMethodAkmedoids | Specify AKMedoids method |
lcMethod-class | lcMethod class |
lcMethodCrimCV | Specify a zero-inflated repeated-measures GBTM method |
lcMethodDtwclust | Specify time series clustering via dtwclust |
lcMethod-estimation | Longitudinal cluster method ('lcMethod') estimation procedure |
lcMethodFeature | Feature-based clustering |
lcMethodFlexmix | Method interface to flexmix() |
lcMethodFlexmixGBTM | Group-based trajectory modeling using flexmix |
lcMethodFunction | Specify a custom method based on a function |
lcMethodFunFEM | Specify a FunFEM method |
lcMethodGCKM | Two-step clustering through latent growth curve modeling and... |
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... |
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... |
lcMethodMixTVEM | Specify a MixTVEM |
lcMethodRandom | Specify a random-partitioning method |
lcMethods | Generate a list of lcMethod objects |
lcMethodStratify | Specify a stratification method |
lcModel | Longitudinal cluster result (*'lcModel'*) |
lcModel-class | 'lcModel' class |
lcModel-data-filters | Data filters for lcModel |
lcModel-make | Cluster-handling functions for lcModel implementations. |
lcModelPartition | Create a lcModel with pre-defined partitioning |
lcModels | Construct a list of 'lcModel' objects |
lcModels-class | 'lcModels': a list of 'lcModel' objects |
lcModelWeightedPartition | Create a lcModel with pre-defined weighted partitioning |
logLik.lcModel | Extract the log-likelihood of a lcModel |
match.call.all | Argument matching with defaults and parent ellipsis expansion |
max.lcModels | Select the lcModel with the highest metric value |
meanNA | Mean ignoring NAs |
metric | Compute internal model metric(s) |
min.lcModels | Select the lcModel with the lowest metric value |
model.data | Extract the model training data |
model.data.lcModel | Extract the model data that was used for fitting |
model.frame.lcModel | Extract model training data |
names-lcMethod-method | lcMethod argument names |
nClusters | Number of clusters |
nIds | Number of trajectories |
nobs.lcModel | Number of observations used for the lcModel fit |
OCC | Odds of correct classification (OCC) |
PAP.adh | Weekly Mean PAP Therapy Usage of OSA Patients in the First 3... |
PAP.adh1y | Biweekly Mean PAP Therapy Adherence of OSA Patients over 1... |
plotClusterTrajectories | Plot cluster trajectories |
plotFittedTrajectories | Plot the fitted trajectories |
plot-lcModel-method | Plot a lcModel |
plot-lcModels-method | Grid plot for a list of models |
plotMetric | Plot one or more internal metrics for all lcModels |
plotTrajectories | Plot the data trajectories |
postFit | 'lcMethod' estimation step: logic for post-processing the... |
postprob | Posterior probability per fitted trajectory |
postprobFromAssignments | Create a posterior probability matrix from a vector of... |
postProbFromObs | Compute the id-specific postprob matrix from a given... |
predictAssignments | Predict the cluster assignments for new trajectories |
predictForCluster | Predict trajectories conditional on cluster membership |
predict.lcModel | lcModel predictions |
predictPostprob | Posterior probability for new data |
preFit | 'lcMethod' estimation step: method preparation logic |
prepareData | 'lcMethod' estimation step: logic for preparing the training... |
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 response variable |
sigma.lcModel | Extract residual standard deviation from a lcModel |
strip | Reduce the memory footprint of an object for serialization |
subset.lcModels | Subsetting a lcModels list based on method arguments |
summary.lcModel | Summarize a lcModel |
test | Test a condition |
test.latrend | Test the implementation of an lcMethod and associated lcModel... |
time.lcModel | Sampling times of a lcModel |
timeVariable | Extract the time variable |
trajectories | Get the trajectories |
trajectoryAssignments | Get the cluster membership of each trajectory |
transformFitted | Helper function for custom lcModel classes implementing... |
transformPredict | Helper function for custom lcModel classes implementing... |
tsframe | Convert a multiple time series matrix to a data.frame |
tsmatrix | Convert a longitudinal data.frame to a matrix |
update.lcMethod | Update a method specification |
update.lcModel | Update a lcModel |
validate | 'lcMethod' estimation step: method argument validation logic |
weighted.meanNA | Weighted arithmetic mean ignoring NAs |
which.weight | Sample an index of a vector weighted by the elements |
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