tronco.kfold.prederr: tronco.kfold.prederr

In TRONCO: TRONCO, an R package for TRanslational ONCOlogy

Description

Perform a k-fold cross-validation using the function bn.cv and scan every node to estimate its prediction error. For details and examples regarding the statistical assesment of an inferred model, we refer to the Vignette Section 7.

Usage

tronco.kfold.prederr(
  x,
  models = names(as.models(x)),
  events = as.events(x),
  runs = 10,
  k = 10,
  cores.ratio = 1,
  silent = FALSE
)

Arguments

x	A reconstructed model (the output of tronco.capri)
models	The names of the selected regularizers (bic, aic or caprese)
events	a list of event
runs	a positive integer number, the number of times cross-validation will be run
k	a positive integer number, the number of groups into which the data will be split
cores.ratio	Percentage of cores to use. coresRate * (numCores - 1)
silent	A parameter to disable/enable verbose messages.

Examples

data(test_model)
tronco.kfold.prederr(test_model, k = 2, runs = 2, cores.ratio = 0)

TRONCO documentation built on Nov. 8, 2020, 5:51 p.m.