mclust interface
# S4 method for lcMethodMclustLLPA
getName(object)# S4 method for lcMethodMclustLLPA
getShortName(object)
# S4 method for lcMethodMclustLLPA
prepareData(method, data, verbose, ...)
# S4 method for lcMethodMclustLLPA
compose(method, envir = NULL)
# S4 method for lcMethodMclustLLPA
fit(method, data, envir, verbose, ...)
# S3 method for lcModelMclustLLPA
predict(object, ..., newdata = NULL, what = "mu", approxFun = approx)
# S3 method for lcModelMclustLLPA
fitted(object, ..., clusters = trajectoryAssignments(object))
# S4 method for lcModelMclustLLPA
postprob(object, ...)
# S4 method for lcModelMclustLLPA
predictPostprob(object, newdata = NULL, ...)
# S4 method for lcModelMclustLLPA
converged(object, ...)
The object to extract the label from.
The lcMethod object.
The data, as a data.frame, on which the model will be trained.
A R.utils::Verbose object indicating the level of verbosity.
Additional arguments.
The environment in which the lcMethod should be evaluated
Optional data frame for which to compute the model predictions. If omitted, the model training data is used. Cluster trajectory predictions are made when ids are not specified. If the clusters are specified under the Cluster column, output is given only for the specified cluster. Otherwise, a matrix is returned with predictions for all clusters.
The distributional parameter to predict. By default, the mean response 'mu' is predicted. The cluster membership predictions can be obtained by specifying what='mb'.
The interpolation function to use for time points not in the feature set.
Optional cluster assignments per id. If unspecified, a matrix is returned containing the cluster-specific predictions per column.