tronco caprese

Reconstruct a progression model using CAPRESE algorithm. For details and examples regarding the inference process and on the algorithm implemented in the package, we refer to the Vignette Section 6.

tronco.caprese(data, lambda = 0.5, silent = FALSE, epos = 0, eneg = 0)

Arguments

data

A TRONCO compliant dataset.

lambda

Coefficient to combine the raw estimate with a correction factor into a shrinkage estimator.

silent

A parameter to disable/enable verbose messages.

epos

Error rate of false positive errors.

eneg

Error rate of false negative errors.

Value

A TRONCO compliant object with reconstructed model

Examples

data(test_dataset_no_hypos)
recon = tronco.caprese(test_dataset_no_hypos)
#> *** Checking input events.
#> *** Inferring a progression model with the following settings.
#> 	Dataset size: n = 40, m = 28.
#> 	Algorithm: CAPRESE with shrinkage coefficient: 0.5.
#> *** Evaluating LogLik informations.
#> The reconstruction has been successfully completed in 00h:00m:00s