Summarise Fold Diagnostics

Combines geographic and environmental diagnostics into a single unified report to evaluate the quality of a cross-validation scheme.

Usage

summarise_fold_diagnostics(geo_diag, env_diag)

# S3 method for class 'FoldsSummary'
print(x, ...)

Arguments

geo_diag

A GeoDiagnostic object.

env_diag

An EnvDiagnostic object.

x

A FoldsSummary object.

...

Additional arguments

Value

• summarise_fold_diagnostics: An object of class FoldsSummary, which inherits from data.frame.

• print: The FoldsSummary object invisibly.

See also

DataFolds-methods for interacting with DataFolds objects.

Other diagnostic tools: EnvDiagnostic-methods, GeoDiagnostic-methods, check_env_balance(), check_folds()

Examples

if (FALSE) { # \dontrun{
library(sf)
library(terra)
library(ggplot2)
library(isdmtools)

# Generate points data
set.seed(42)
presence_data <- data.frame(
  x = runif(100, 0, 4),
  y = runif(100, 6, 13),
  site = rbinom(100, 1, 0.6)
) |> st_as_sf(coords = c("x", "y"), crs = 4326)

count_data <- data.frame(
  x = runif(50, 0, 4),
  y = runif(50, 6, 13),
  count = rpois(50, 5)
) |> st_as_sf(coords = c("x", "y"), crs = 4326)

datasets_list <- list(Presence = presence_data, Count = count_data)

# Environmental data
set.seed(42)
r <- rast(extent = c(0, 4, 6, 13), nrow = 100, ncol = 100, crs = "epsg:4326")
r[] <- rnorm(ncell(r))
rtmp <- r
rtmp[] <- runif(ncell(r), 5, 10)

r_stk <- c(r, rtmp + r)
names(r_stk) <- c("cov1", "cov2")

# Create Folds
folds <- create_folds(datasets_list, cv_method = "cluster")

# Spatial diagnostics
spat_diag <- check_folds(folds, plot = TRUE)

# Environmental diagnostics
env_diag <- suppressWarnings(check_env_balance(
  folds,
  covariates = r_stk,
  n_background = 5000
))

# Combined diagnostics
sum_diag <- summarise_fold_diagnostics(spat_diag, env_diag)
print(sum_diag)
} # }