partition_disc {sperrorest} | R Documentation |
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, ...)
Arguments
data |
|
coords |
vector of length 2 defining the variables in |
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 |
seed1 |
|
return_train |
If |
prob |
optional argument to sample. |
replace |
optional argument to sample: sampling with or without replacement? |
repetition |
see |
... |
arguments to be passed to |
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.
Note
Test area discs are centered at (random) samples, not at general
random locations. Test area discs may (and likely will) overlap independently
of the value of replace
. replace
only controls the replacement
of the center point of discs when drawing center points from the samples.
radius < 0
does leave-one-out resampling with an optional buffer.
radius = 0
is similar except that samples with identical coordinates
would fall within the test area 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)