crimCV interface
# S4 method for lcMethodCrimCV
getArgumentDefaults(object)# S4 method for lcMethodCrimCV
getArgumentExclusions(object)
# S4 method for lcMethodCrimCV
getName(object)
# S4 method for lcMethodCrimCV
getShortName(object)
# S4 method for lcMethodCrimCV
prepareData(method, data, verbose, ...)
# S4 method for lcMethodCrimCV
fit(method, data, envir, verbose, ...)
# S4 method for lcModelCrimCV
predictForCluster(object, newdata, cluster, what = "mu", ...)
# S4 method for lcModelCrimCV
postprob(object)
# S3 method for lcModelCrimCV
logLik(object, ...)
# S3 method for lcModelCrimCV
coef(object, ...)
# S4 method for lcModelCrimCV
converged(object)
The lcMethod or lcModel object.
An object inheriting from lcMethod with all its arguments having been evaluated and finalized.
A data.frame representing the transformed training data.
A R.utils::Verbose object indicating the level of verbosity.
Additional arguments.
The environment containing variables generated by prepareData() and preFit().
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.
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'.