sperrorest (version 3.0.5)

represampling_bootstrap: Non-spatial bootstrap resampling

Description

represampling_bootstrap draws a bootstrap random sample (with replacement) from data.

Usage

represampling_bootstrap(
  data,
  coords = c("x", "y"),
  nboot = nrow(data),
  repetition = 1,
  seed1 = NULL,
  oob = FALSE
)

Value

A represampling object. This is a (named) list containing length(repetition). resampling objects. Each of these contains only one list with indices of training and test samples. Indices are row indices for data.

Arguments

data

data.frame containing at least the columns specified by coords

coords

vector of length 2 defining the variables in data that contain the x and y coordinates of sample locations.

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 repetition = c(1:100) to obtain (the 'first') 100 repetitions, and repetition = c(101:200) to obtain a different set of 100 repetitions.

seed1

seed1+i is the random seed that will be used by set.seed in repetition i (i in repetition) to initialize the random number generator before sampling from the data set.

oob

logical (default FALSE): if TRUE, use the out-of-bag sample as the test sample; if FALSE, draw a second bootstrap sample of size nboot independently to obtain a test sample.

Examples

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)