latrend: latrendCV – R documentation

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latrendCV

Cluster longitudinal data over k folds

Description

Apply k-fold cross validation for internal cluster validation. Creates k random subsets ("folds") from the data, estimating a model for each of the k-1 combined folds.

Usage

latrendCV(
  method,
  data,
  folds = 10,
  seed = NULL,
  parallel = FALSE,
  errorHandling = "stop",
  envir = NULL,
  verbose = getOption("latrend.verbose")
)

Arguments

`method`	The `lcMethod` object specifying the longitudinal cluster method to apply.
`data`	A `data.frame`.
`folds`	The number of folds. Ten folds by default.
`seed`	The seed to use. Optional.
`parallel`	Whether to enable parallel evaluation. See latrend-parallel.
`errorHandling`	Whether to `"stop"` on an error, or to `"remove'` evaluations that raised an error.
`envir`	The `environment` in which to evaluate the method arguments. Note that this only applies to `data` when `data` is a `call`.
`verbose`	The level of verbosity. Either an object of class `Verbose` (see R.utils::Verbose for details), a `logical` indicating whether to show basic computation information, a `numeric` indicating the verbosity level (see Verbose), or one of `c('info', 'fine', 'finest')`.

Value

A lcModels object of containing the folds training models.

Examples

data(latrendData)
method <- lcMethodKML("Y", id = "Id", time = "Time")
model <- latrendCV(method, latrendData, folds = 5)

model <- latrendCV(method, subset(latrendData, Time < .5), folds = 5, seed = 1)

latrend

A Framework for Clustering Longitudinal Data

v1.1.2

GPL (>= 2)

Authors

Initial release

2021-04-14