interface-mixtools: mixtools interface

Description Usage Arguments See Also

Description

mixtools interface

Usage

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

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

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

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

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

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

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

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

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

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

## S3 method for class 'lcModelMixtoolsGMM'
coef(object, ...)

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

## S4 method for signature 'lcModelMixtoolsRM'
clusterTrajectories(
  object,
  at = time(object),
  what = "mu",
  se = TRUE,
  ci = c(0.025, 0.975),
  ...
)

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

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

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

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.

envir

The environment in which the lcMethod should be evaluated

verbose

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

...

Additional arguments.

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'.

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.

se

Whether to compute the standard error of the prediction.

ci

The confidence interval to compute.

See Also

lcMethodMixtoolsGMM lcMethodMixtoolsNPRM regmixEM.mixed npEM


latrend documentation built on April 14, 2021, 5:08 p.m.