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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 |
| 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 |
| 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 |
| 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 | Compute external model metric(s) |
| externalMetric-method | Compute external model metric(s) |
| 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 |
| 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 |
| ids | Get the unique ids included in this model |
| idVariable | Extract the trajectory identifier variable |
| idVariable-method | Extract the trajectory identifier variable |
| 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 |
| 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 |
| names-method | lcMethod class |
| nClusters | Number of clusters |
| nIds | Number of strata |
| nobs.lcModel | Extract the number of observations from a lcModel |
| 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 |
| qqPlot | Quantile-quantile plot |
| qqPlot-method | Quantile-quantile plot |
| residuals.lcModel | Extract lcModel residuals |
| responseVariable | Extract the response variable |
| responseVariable-method | Extract the response variable |
| 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 |
| 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 |
| update.lcMethod | Update a method specification |
| update.lcModel | Update a lcModel |
| validate | lcMethod class |
| validate-method | lcMethod class |
| which.weight | Sample an index of a vector weighted by the elements |
| $-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 |