Draw bootstrap samples of observations or groups of observations and specify which bootstrap estimator of prediction error to compute.
bootSamples(n, R = 1, type = c("0.632", "out-of-bag"), grouping = NULL)
an integer giving the number of observations for which to draw
bootstrap samples. This is ignored if grouping
is supplied in
order to respect the group structure of the data in the bootstrap samples.
an integer giving the number of bootstrap samples.
a character string specifying a bootstrap estimator. Possible
values are "0.632"
(the default), or "out-of-bag"
.
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.
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.
# NOT RUN {
set.seed(1234) # set seed for reproducibility
bootSamples(20)
bootSamples(20, R = 10)
# }
Run the code above in your browser using DataLab