R: lcmm interface

getArgumentDefaults,lcMethodLcmmGMM-method

R 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'`.

lcmm interface

Description

Usage

Arguments

See Also