funFEM interface
# S4 method for lcMethodFunFEM
getName(object)# S4 method for lcMethodFunFEM
getShortName(object)
# S4 method for lcMethodFunFEM
preFit(method, data, envir, verbose, ...)
# S4 method for lcMethodFunFEM
fit(method, data, envir, verbose, ...)
# S3 method for lcModelFunFEM
fitted(object, ..., clusters = trajectoryAssignments(object))
# S3 method for lcModelFunFEM
predict(object, ..., newdata = NULL, what = "mu", approxFun = approx)
# S4 method for lcModelFunFEM
postprob(object, ...)
# S3 method for lcModelFunFEM
coef(object, ...)
# S3 method for lcModelFunFEM
logLik(object, ...)
# S4 method for lcModelFunFEM
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.
The environment in which the lcMethod should be evaluated
A R.utils::Verbose object indicating the level of verbosity.
Additional arguments.
Optional cluster assignments per id. If unspecified, a matrix is returned containing the cluster-specific predictions per column.
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.