interface-mixtools: mixtools interface

In latrend: A Framework for Clustering Longitudinal Data

mixtools interface

Description

mixtools interface

Usage

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

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

## S4 method for signature 'lcMethodMixtoolsGMM'
getCitation(object, ...)

## 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'
getArgumentDefaults(object)

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

## S4 method for signature 'lcMethodMixtoolsNPRM'
getCitation(object, ...)

## 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.
...	Not used.
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().
verbose	A R.utils::Verbose object indicating the level of verbosity.
newdata	A data.frame of trajectory data for which to compute trajectory assignments.
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	A ⁠numeric vector⁠ of the times at which to compute the cluster trajectories.
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 May 29, 2024, 8:51 a.m.