generate_cv_folds: Generate cross-validation folds

In glossa: User-Friendly 'shiny' App for Bayesian Species Distribution Models

Generate cross-validation folds

Description

Creates cross-validation fold assignments for presence-absence or presence-only data, supporting three types of strategies: k-fold, spatial blocks (through blockCV R package), and temporal blocks.

Usage

generate_cv_folds(
  data,
  method = "k-fold",
  block_method = "predictors_autocorrelation",
  block_size = NULL,
  k = 10,
  predictor_raster = NULL,
  model_residuals = NULL,
  coords = c("decimalLongitude", "decimalLatitude")
)

Arguments

data	A 'data.frame' with at least presence-absence data ('pa'), coordinates, and optionally a 'timestamp'.
method	The cross-validation strategy. One of: '"k-fold"', '"spatial_blocks"', '"temporal_blocks"'.
block_method	For spatial blocks, how to determine block size. One of: '"residuals_autocorrelation"', '"predictors_autocorrelation"', '"manual"'.
block_size	Numeric. Manual block size in meters (used if 'block_method = "manual"').
k	Integer. Number of folds to generate.
predictor_raster	A 'terra::SpatRaster' used for estimating spatial autocorrelation (only needed if 'block_method = "predictors_autocorrelation"').
model_residuals	A 'data.frame' with residuals and coordinates (only needed if 'block_method = "residuals_autocorrelation"').
coords	A character vector of length 2 indicating the longitude and latitude column names.

Value

A list with the following elements:

folds

A vector of fold assignments (one per row in 'data').

method

The CV method used.

block_method

The spatial block size method (if applicable).

block_size

The estimated or manual block size (in meters), if spatial blocks were used.

glossa documentation built on June 8, 2025, 1:20 p.m.