latrend (version 1.6.2)

interface-mixtools: mixtools interface

Description

mixtools interface

Usage

# S4 method for lcMethodMixtoolsGMM
getArgumentDefaults(object)
# S4 method for lcMethodMixtoolsGMM
getArgumentExclusions(object)
# S4 method for lcMethodMixtoolsGMM
getCitation(object, ...)
# S4 method for lcMethodMixtoolsGMM
getName(object)
# S4 method for lcMethodMixtoolsGMM
getShortName(object)
# S4 method for lcMethodMixtoolsGMM
preFit(method, data, envir, verbose, ...)
# S4 method for lcMethodMixtoolsGMM
fit(method, data, envir, verbose, ...)
# S4 method for lcMethodMixtoolsNPRM
getArgumentDefaults(object)
# S4 method for lcMethodMixtoolsNPRM
getArgumentExclusions(object)
# S4 method for lcMethodMixtoolsNPRM
getCitation(object, ...)
# S4 method for lcMethodMixtoolsNPRM
getName(object)
# S4 method for lcMethodMixtoolsNPRM
getShortName(object)
# S4 method for lcMethodMixtoolsNPRM
fit(method, data, envir, verbose, ...)
# S4 method for lcModelMixtoolsGMM
predictForCluster(object, newdata, cluster, what = "mu", ...)
# S4 method for lcModelMixtoolsGMM
postprob(object, ...)
# S3 method for lcModelMixtoolsGMM
logLik(object, ...)
# S3 method for lcModelMixtoolsGMM
coef(object, ...)
# S3 method for lcModelMixtoolsGMM
sigma(object, ...)
# S4 method for lcModelMixtoolsRM
clusterTrajectories(
  object,
  at = time(object),
  what = "mu",
  se = TRUE,
  ci = c(0.025, 0.975),
  ...
)
# S4 method for lcModelMixtoolsRM
postprob(object, ...)
# S3 method for lcModelMixtoolsRM
logLik(object, ...)
# S4 method for 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