flexmix interface
# S4 method for lcMethodFlexmix
getName(object)# S4 method for lcMethodFlexmix
getShortName(object)
# S4 method for lcMethodFlexmix
preFit(method, data, envir, verbose, ...)
# S4 method for lcMethodFlexmix
fit(method, data, envir, verbose, ...)
# S4 method for lcMethodFlexmixGBTM
getName(object)
# S4 method for lcMethodFlexmixGBTM
getShortName(object)
# S4 method for lcMethodFlexmixGBTM
preFit(method, data, envir, verbose)
# S3 method for lcModelFlexmix
predict(object, ..., newdata = NULL, what = "mu")
# S3 method for lcModelFlexmix
fitted(object, ..., clusters = trajectoryAssignments(object))
# S4 method for lcModelFlexmix
postprob(object, ...)
# S3 method for lcModelFlexmix
logLik(object, ...)
# S3 method for lcModelFlexmix
coef(object, ...)
# S4 method for lcModelFlexmix
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 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'.
Optional cluster assignments per id. If unspecified, a matrix is returned containing the cluster-specific predictions per column.