Description Usage Arguments Value Note Author(s) References See Also Examples
Draw bootstrap samples of observations or groups of observations and specify which bootstrap estimator of prediction error to compute.
1 2  bootSamples(n, R = 1, type = c("0.632", "outofbag"),
grouping = NULL)

n 
an integer giving the number of observations for
which to draw bootstrap samples. This is ignored if

R 
an integer giving the number of bootstrap samples. 
type 
a character string specifying a bootstrap
estimator. Possible values are 
grouping 
a factor specifying groups of observations. If supplied, the groups are resampled rather than individual observations such that all observations within a group belong either to the bootstrap sample or the test data. 
An object of class "bootSamples"
with the
following components:
n 
an integer giving the number of observations or groups. 
R 
an integer giving the number of bootstrap samples. 
subsets 
an integer matrix in which each column contains the indices of the observations or groups in the corresponding bootstrap sample. 
grouping 
a list giving the indices of the observations belonging to each group. This is only returned if a grouping factor has been supplied. 
This is a simple wrapper function for
perrySplits
with a control object generated
by bootControl
.
Andreas Alfons
Efron, B. (1983) Estimating the error rate of a prediction rule: improvement on crossvalidation. Journal of the American Statistical Association, 78(382), 316–331.
perrySplits
, bootControl
,
cvFolds
, randomSplits
1 2 3  set.seed(1234) # set seed for reproducibility
bootSamples(20)
bootSamples(20, R = 10)

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