represampling_bootstrap
draws a bootstrap random sample
(with replacement) from data
.
represampling_bootstrap(data, coords = c("x", "y"), nboot = nrow(data), repetition = 1, seed1 = NULL, oob = FALSE)
data |
|
---|---|
coords | vector of length 2 defining the variables in |
nboot | Size of bootstrap sample |
repetition | numeric vector: cross-validation repetitions
to be generated. Note that this is not the number of repetitions,
but the indices of these repetitions. E.g., use |
seed1 |
|
oob | logical (default |
A represampling object. This is a (named) list
containing length(repetition)
.
resampling objects. Each of these contains only one list with
indices of train
ing and test
samples.
Indices are row indices for data
.
data(ecuador) # only 10 bootstrap repetitions, normally use >=100: parti <- represampling_bootstrap(ecuador, repetition = 10) # plot(parti, ecuador) # careful: overplotting occurs # because some samples are included in both the training and # the test sample (possibly even multiple times)