stratify_spatial: Split data for k-fold spatially stratified cross validation

In bmaitner/pbsdm: Small Sample Size Species Distribution Modeling

Split data for k-fold spatially stratified cross validation

Description

Splitting tool for cross-validation

Usage

stratify_spatial(occurrence_sf, nfolds = NULL, nsubclusters = NULL)

Arguments

occurrence_sf	a sf object containing occurrence points
nfolds	number of desired output folds. Default value of NULL makes a reasonable guess based on sample size.
nsubclusters	intermediate number of clusters randomly split into nfolds. Default value of NULL makes a reasonable guess based on sample size. If you specify this manually, it should be an integer multiple of nfolds.

Details

See Examples.

Value

Returns a SpatialPoints dataframe with the data.frame containing fold designation for each point.

Author(s)

Cory Merow [e-mail]

Examples

{

# load in sample data

 library(S4DM)
 library(terra)
 library(sf)

 # occurrence points
   data("sample_points")
   occurrences <- sample_points


 occurrences <- st_as_sf(x = occurrences,coords = c(1,2))

manual <- stratify_spatial(occurrence_sf = occurrences,nfolds = 5,nsubclusters = 5)
default <- stratify_spatial(occurrence_sf = occurrences)


}

bmaitner/pbsdm documentation built on Feb. 8, 2025, 2:27 p.m.