interface-custom: function interface

clusterTrajectories,lcModelPartition-methodR Documentation

function interface

Description

function interface

Usage

## S4 method for signature 'lcModelPartition'
clusterTrajectories(
  object,
  at = time(object),
  center = object@center,
  approxFun = approx,
  ...
)

## S4 method for signature 'lcModelPartition'
converged(object, ...)

## S4 method for signature 'lcModelPartition'
getName(object, ...)

## S4 method for signature 'lcModelPartition'
getShortName(object, ...)

## S4 method for signature 'lcModelPartition'
postprob(object, ...)

## S4 method for signature 'lcMethodFunction'
getArgumentDefaults(object)

## S4 method for signature 'lcMethodFunction'
getName(object)

## S4 method for signature 'lcMethodFunction'
getShortName(object)

## S4 method for signature 'lcMethodFunction'
prepareData(method, data, verbose)

## S4 method for signature 'lcMethodFunction'
fit(method, data, envir, verbose)

## S4 method for signature 'lcMethodRandom'
getArgumentDefaults(object)

## S4 method for signature 'lcMethodRandom'
getName(object)

## S4 method for signature 'lcMethodRandom'
getShortName(object)

## S4 method for signature 'lcMethodRandom'
fit(method, data, envir, verbose, ...)

## S4 method for signature 'lcModelStratify'
converged(object, ...)

## S4 method for signature 'lcModelStratify'
predictPostprob(object, newdata = NULL, ...)

## S4 method for signature 'lcModelWeightedPartition'
clusterTrajectories(
  object,
  at = time(object),
  center = weighted.meanNA,
  approxFun = approx,
  ...
)

## S4 method for signature 'lcModelWeightedPartition'
converged(object, ...)

## S4 method for signature 'lcModelWeightedPartition'
getName(object, ...)

## S4 method for signature 'lcModelWeightedPartition'
getShortName(object, ...)

## S4 method for signature 'lcModelWeightedPartition'
postprob(object, ...)

Arguments

object

The lcMethod or lcModel object.

center

The function to use to compute the cluster trajectory center at the respective moment in time.

...

Additional arguments.

method

An object inheriting from lcMethod with all its arguments having been evaluated and finalized.

data

A data.frame representing the transformed training data.

verbose

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

envir

The environment containing variables generated by prepareData() and preFit().

newdata

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

See Also

lcMethodRandom lcMethodStratify lcModelPartition lcModelWeightedPartition


latrend documentation built on March 31, 2023, 5:45 p.m.