bootstrap: Perform bootstrap.

In tavazzie/bnstructScore: Bayesian Network Structure Learning from Data with Missing Values

Description

Create a list of num.boots samples of the original dataset.

Usage

bootstrap(object, num.boots = 100, seed = 0, imputation = FALSE, k.impute = 10)

## S4 method for signature 'BNDataset'
bootstrap(object, num.boots = 100, seed = 0, imputation = FALSE, k.impute = 10)

Arguments

object	the BNDataset object.
num.boots	number of sampled datasets for bootstrap.
seed	random seed.
imputation	TRUE if imputation has to be performed. Default is FALSE.
k.impute	number of neighbours to be used; for discrete variables we use mode, for continuous variables the median value is instead taken (useful only if imputation == TRUE).

Examples

## Not run: 
dataset <- BNDataset("file.data", "file.header")
dataset <- bootstrap(dataset, num.boots = 1000)

## End(Not run)

tavazzie/bnstructScore documentation built on Dec. 23, 2021, 7:47 a.m.