interface-lcmm: lcmm interface

getArgumentDefaults,lcMethodLcmmGMM-methodR Documentation

lcmm interface

Description

lcmm interface

Usage

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

## S4 method for signature 'lcMethodLcmmGMM'
getArgumentExclusions(object)

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

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

## S4 method for signature 'lcMethodLcmmGMM'
validate(method, data, envir = NULL, ...)

## S4 method for signature 'lcMethodLcmmGMM'
preFit(method, data, envir, verbose, ...)

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

## S4 method for signature 'lcMethodLcmmGMM'
responseVariable(object, ...)

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

## S4 method for signature 'lcMethodLcmmGBTM'
getArgumentExclusions(object)

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

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

## S4 method for signature 'lcMethodLcmmGBTM'
preFit(method, data, envir, verbose, ...)

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

## S4 method for signature 'lcMethodLcmmGBTM'
responseVariable(object, ...)

## S3 method for class 'lcModelLcmmGMM'
fitted(object, ..., clusters = trajectoryAssignments(object))

## S4 method for signature 'lcModelLcmmGMM'
predictForCluster(object, newdata, cluster, what = "mu", ...)

## S3 method for class 'lcModelLcmmGMM'
model.matrix(object, ..., what = "mu")

## S3 method for class 'lcModelLcmmGMM'
logLik(object, ...)

## S3 method for class 'lcModelLcmmGMM'
sigma(object, ...)

## S3 method for class 'lcModelLcmmGMM'
nobs(object, ...)

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

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

Arguments

object

The lcMethod or lcModel object.

method

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

data

A data.frame representing the transformed training data.

envir

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

...

Additional arguments.

verbose

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

clusters

Optional cluster assignments per id. If unspecified, a matrix is returned containing the cluster-specific predictions per column.

newdata

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.

cluster

The cluster name (as character) to predict for.

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'.

See Also

lcMethodLcmmGBTM lcMethodLcmmGMM lcmm-package


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