represampling_disc_bootstrap
performs a spatial block bootstrap by
resampling at the level of rectangular partitions or 'tiles' generated by
partition_tiles
.
represampling_disc_bootstrap(data, coords = c("x", "y"), nboot, repetition = 1, seed1 = NULL, oob = FALSE, ...)
data |
|
---|---|
coords | vector of length 2 defining the variables in |
nboot | number of bootstrap samples; you may specify different values
for the training 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 |
... | additional arguments to be passed to partition_disc;
note that a |
Performs nboot
out of nrow(data)
resampling of circular
discs. This is an overlapping spatial block bootstrap where the
blocks are circular.
data(ecuador) # Overlapping disc bootstrap: parti <- represampling_disc_bootstrap(ecuador, radius = 200, nboot = 20, oob = FALSE) # plot(parti, ecuador) # Note that a 'buffer' argument would make no difference because boostrap # sets of discs are drawn independently for the training and test sample. # # Overlapping disc bootstrap for training sample, out-of-bag sample as test # sample: parti <- represampling_disc_bootstrap(ecuador, radius = 200, buffer = 200, nboot = 10, oob = TRUE) # plot(parti,ecuador)