Cluster longitudinal data using bootstrapping
Performs bootstrapping, generating samples from the given data at the id level, fitting a lcModel to each sample.
latrendBoot(
method,
data,
samples = 50,
seed = NULL,
parallel = FALSE,
errorHandling = "stop",
envir = NULL,
verbose = getOption("latrend.verbose")
)method |
The |
data |
A |
samples |
The number of bootstrap samples to evaluate. |
seed |
The seed to use. Optional. |
parallel |
Whether to enable parallel evaluation. See latrend-parallel. |
errorHandling |
Whether to |
envir |
The |
verbose |
The level of verbosity. Either an object of class |
A lcModels object of length samples.
Other longitudinal cluster fit functions:
latrendBatch(),
latrendCV(),
latrendRep(),
latrend()
Other validation methods:
createTestDataFolds(),
createTestDataFold(),
createTrainDataFolds(),
latrendCV(),
lcModel-data-filters
data(latrendData)
method <- lcMethodKML("Y", id = "Id", time = "Time")
model <- latrendBoot(method, latrendData, samples = 10)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.