Random Spatial Split

Creates a random spatial split serving as a baseline for comparison with spatial cross-validation methods. This represents traditional random cross-validation without spatial considerations.

Usage

spatial_split(data, x = NULL, y = NULL, k = 5, seed = NULL)

Arguments

data

Spatial observations (data.frame or sf object)

x

Name of the x coordinate column (required for data.frame, ignored for sf)

y

Name of the y coordinate column (required for data.frame, ignored for sf)

k

Number of folds (default: 5)

seed

Random seed for reproducibility (default: NULL)

Value

An object of class "spatial_folds" containing fold assignments

Details

This method performs standard random k-fold cross-validation without any spatial constraints. It serves as a baseline to compare against spatial cross-validation methods and demonstrate the impact of spatial dependence on model evaluation.

See also

Other spatial cross-validation functions: spatial_block_folds(), spatial_buffer_folds(), spatial_cluster_folds(), spatial_folds()

Examples

if (FALSE) { # \dontrun{
data(sample_spatial_data)
folds <- spatial_split(
  data = sample_spatial_data,
  x = "longitude",
  y = "latitude",
  k = 5
)
} # }