flexmix interface
# S4 method for lcMethodFlexmix
getArgumentDefaults(object)# S4 method for lcMethodFlexmix
getArgumentExclusions(object)
# S4 method for lcMethodFlexmix
getCitation(object, ...)
# 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
getArgumentDefaults(object)
# S4 method for lcMethodFlexmixGBTM
getArgumentExclusions(object)
# 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
fitted(object, ..., clusters = trajectoryAssignments(object))
# S4 method for lcModelFlexmix
predictForCluster(object, newdata, cluster, what = "mu", ...)
# 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 lcModel object.
Not used.
An object inheriting from lcMethod with all its arguments having been evaluated and finalized.
A data.frame representing the transformed training data.
The environment containing variables generated by prepareData() and preFit().
A R.utils::Verbose object indicating the level of verbosity.
Optional cluster assignments per id. If unspecified, a matrix is returned containing the cluster-specific predictions per column.
A data.frame of trajectory data for which to compute trajectory assignments.
The cluster name (as character) to predict for.
The distributional parameter to predict. By default, the mean response 'mu' is predicted. The cluster membership predictions can be obtained by specifying what = 'mb'.
lcMethodFlexmix flexmix