sperrorest (version 3.0.5)

partition_disc: Leave-one-disc-out cross-validation and leave-one-out cross-validation

Description

partition_disc partitions the sample into training and tests set by selecting circular test areas (possibly surrounded by an exclusion buffer) and using the remaining samples as training samples (leave-one-disc-out cross-validation). partition_loo creates training and test sets for leave-one-out cross-validation with (optional) buffer.

Usage

partition_disc(
  data,
  coords = c("x", "y"),
  radius,
  buffer = 0,
  ndisc = nrow(data),
  seed1 = NULL,
  return_train = TRUE,
  prob = NULL,
  replace = FALSE,
  repetition = 1
)
partition_loo(data, ndisc = nrow(data), replace = FALSE, ...)

Value

A represampling object. Contains length(repetition)

resampling

objects. Each of these contains ndisc lists with indices of test and (if return_train = TRUE) training sets.

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.

radius

radius of test area discs; performs leave-one-out resampling if radius <0.

buffer

radius of additional 'neutral area' around test area discs that is excluded from training and test sets; defaults to 0, i.e. all samples are either in the test area or in the training area.

ndisc

Number of discs to be randomly selected; each disc constitutes a separate test set. Defaults to nrow(data), i.e. one disc around each sample.

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.

return_train

If FALSE, returns only test sample; if TRUE, also the training area.

prob

optional argument to sample.

replace

optional argument to sample: sampling with or without replacement?

repetition

see partition_cv; however, see Note below: repetition should normally be = 1 in this function.

...

arguments to be passed to partition_disc

References

Brenning, A. 2005. Spatial prediction models for landslide hazards: review, comparison and evaluation. Natural Hazards and Earth System Sciences, 5(6): 853-862.

See Also

sperrorest, partition_cv, partition_kmeans

Examples

data(ecuador)
parti <- partition_disc(ecuador,
  radius = 200, buffer = 200,
  ndisc = 5, repetition = 1:2
)
# plot(parti,ecuador)
summary(parti)

# leave-one-out with buffer:
parti.loo <- partition_loo(ecuador, buffer = 200)
summary(parti)