represampling_disc_bootstrap performs a spatial block
bootstrap by resampling at the level of rectangular partitions or 'tiles'
represampling_disc_bootstrap( data, coords = c("x", "y"), nboot, repetition = 1, seed1 = NULL, oob = FALSE, ... )
vector of length 2 defining the variables in
number of bootstrap samples; you may specify different values
for the training sample (
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
additional arguments to be passed to partition_disc; note that a
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)