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 | bootSamples(n, R = 1, type = c("0.632", "out-of-bag"), 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 cross-validation. 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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