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latrend (version 1.1.0)

interface-custom: custom interface

Description

custom interface

Usage

# S4 method for lcMethodCustom
getName(object)
# S4 method for lcMethodCustom
getShortName(object)
# S4 method for lcMethodCustom
prepareData(method, data, verbose)
# S4 method for lcMethodCustom
fit(method, data, envir, verbose)
# S4 method for lcModelCustom
getName(object, ...)
# S4 method for lcModelCustom
getShortName(object, ...)
# S4 method for lcModelCustom
converged(object, ...)
# S4 method for lcModelCustom
postprob(object, ...)
# S3 method for lcModelCustom
predict(object, ..., newdata = NULL, what = "mu")
# S4 method for lcModelCustom
predictPostprob(object, newdata = NULL, ...)
# S4 method for lcModelCustom
clusterTrajectories(object, at = time(object), ...)
# S4 method for lcModelCustom
trajectories(
  object,
  at = time(object),
  what = "mu",
  clusters = trajectoryAssignments(object),
  ...
)
# S4 method for lcMethodRandom
getName(object)
# S4 method for lcMethodRandom
getShortName(object)
# S4 method for lcMethodRandom
fit(method, data, envir, verbose, ...)
# S4 method for lcModelPartition
clusterTrajectories(object, at = time(object), ...)
# S4 method for lcModelPartition
converged(object, ...)
# S4 method for lcModelPartition
getName(object, ...)
# S4 method for lcModelPartition
getShortName(object, ...)
# S4 method for lcModelPartition
postprob(object, ...)
# S4 method for lcModelStratify
clusterTrajectories(object, at = time(object), ...)
# S4 method for lcModelStratify
converged(object, ...)
# S4 method for lcModelStratify
postprob(object, ...)
# S4 method for lcModelStratify
predictPostprob(object, newdata = NULL, ...)

Arguments

object

The object to extract the label from.

method

The lcMethod object.

data

The data, as a data.frame, on which the model will be trained.

verbose

A R.utils::Verbose object indicating the level of verbosity.

envir

The environment in which the lcMethod should be evaluated

...

Additional arguments.

newdata

Optional data frame for which to compute the posterior probability. If omitted, the model training data is used.

what

The distributional parameter to predict. By default, the mean response 'mu' is predicted. The cluster membership predictions can be obtained by specifying what = 'mb'.

at

An optional vector, list or data frame of covariates at which to compute the cluster trajectory predictions. If a vector is specified, this is assumed to be the time covariate. Otherwise, a named list or data frame must be provided.

clusters

The cluster assignments for the strata to base the trajectories on.

See Also

lcMethodCustom lcModelCustom lcMethodRandom lcMethodStratify lcModelPartition lcModelWeightedPartition