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latrend (version 1.0.1)

interface-mixtools: mixtools interface

Description

mixtools interface

Usage

# 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
getName(object)
# S4 method for lcMethodMixtoolsNPRM
getShortName(object)
# S4 method for lcMethodMixtoolsNPRM
fit(method, data, envir, verbose, ...)
# S4 method for lcModelMixtoolsGMM
postprob(object, ...)
# S3 method for lcModelMixtoolsGMM
predict(object, ..., newdata = NULL, what = "mu")
# S3 method for lcModelMixtoolsGMM
logLik(object, ...)
# S3 method for lcModelMixtoolsGMM
coef(object, ...)
# S3 method for lcModelMixtoolsGMM
sigma(object, ...)
# S3 method for lcModelMixtoolsRM
predict(
  object,
  ...,
  newdata = NULL,
  what = "mu",
  se = TRUE,
  ci = c(0.025, 0.975),
  approxFun = approx
)
# S3 method for lcModelMixtoolsRM
fitted(object, ..., clusters)
# S4 method for lcModelMixtoolsRM
postprob(object, ...)
# S3 method for lcModelMixtoolsRM
logLik(object, ...)
# S4 method for 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. If the clusters are specified under the Cluster column, output is given only for the specified cluster. Otherwise, a matrix is returned with predictions for all clusters.

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'.

se

Whether to compute the standard error of the prediction.

ci

The confidence interval to compute.

approxFun

The interpolation function to use for time points not in the feature set.

clusters

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

See Also

lcMethodMixtoolsGMM lcMethodMixtoolsNPRM regmixEM.mixed npEM