Fit a single H3SDM species distribution model

Fits a single species distribution model (SDM) workflow using spatial cross-validation. Computes performance metrics for each fold and fits the final model to the entire dataset. Optionally calculates post-hoc metrics such as True Skill Statistic (TSS) and Boyce index.

Usage

h3sdm_fit_model(
  sdm_workflow,
  data_split,
  presence_data = NULL,
  truth_col = "presence",
  pred_col = ".pred_1"
)

Arguments

sdm_workflow: A workflow object from h3sdm_workflow() or manually created.
data_split: A resampling object (e.g., from vfold_cv() or h3sdm_spatial_cv()) used for cross-validation.
presence_data: Optional sf or tibble object containing presence locations to compute Boyce index.
truth_col: Character string specifying the name of the column containing the true presence/absence values. Defaults to "presence".
pred_col: Character string specifying the name of the column containing predicted probabilities. Defaults to ".pred_1".

Value

A list containing:

cv_model: Cross-validation results (tune_results).
final_model: Fitted workflow on the full dataset.
metrics: A tibble of performance metrics including ROC AUC, accuracy, sensitivity, specificity, F1-score, Kappa, TSS, and Boyce index.

Examples

if (FALSE) { # \dontrun{
library(h3sdm)
library(tidymodels)
library(sf)

# Simular datos espaciales
coords <- cbind(
  x = runif(20, -100, 100),
  y = runif(20, -100, 100)
)
dat_sf <- st_as_sf(
  data.frame(
    x1 = rnorm(20),
    x2 = rnorm(20),
    presence = factor(sample(0:1, 20, replace = TRUE))
  ),
  coords = c("x", "y"),
  crs = 4326
)

# Crear receta
rec <- recipe(presence ~ x1 + x2, data = dat_sf)

# Modelo simple
mod_spec <- logistic_reg() %>%
  set_engine("glm") %>%
  set_mode("classification")

# Crear workflow
my_workflow <- workflow() %>%
  add_model(mod_spec) %>%
  add_recipe(rec)

# Resampling espacial
my_cv <- vfold_cv(dat_sf, v = 3)

# Ajustar modelo
fitted <- h3sdm_fit_model(
  sdm_workflow  = my_workflow,
  data_split    = my_cv,
  presence_data = dat_sf
)
} # }