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Fit a parametric spatial correlation model to the empirical correlogram

Source: R/stochastic_fields.R
hm_fit_correlation_model.Rd

Fits Matérn, Exponential, Gaussian, and/or Spherical covariance families to the correlogram from [hm_empirical_correlogram()] by weighted least squares (Eq. 6–7 of Clavijo Mesa et al., 2026, SF paper). Selects the best family by RMSE, matching Table 1 of that paper.

Usage

hm_fit_correlation_model(
  corg,
  families = c("matern", "exponential", "gaussian", "spherical"),
  max_dist = NULL
)

Arguments

corg

data.frame from [hm_empirical_correlogram()].

families

Covariance families to fit. Any subset of c("matern", "exponential", "gaussian", "spherical"). Defaults to all four.

max_dist

Maximum distance in km to include. Defaults to the full correlogram range.

Value

An hm_corrmodel list with best_family, best_params, best_rmse, all_fits, and corg.

References

Clavijo Mesa, M.V., Broggi, M., Di Maio, F. & Zio, E. (2026). International Journal of Disaster Risk Reduction, 141, 106172.

See also

[hm_empirical_correlogram()], [hm_simulate_sf_kle()]

Examples

if (FALSE) { # \dontrun{
corg  <- hm_empirical_correlogram(tau, D)
model <- hm_fit_correlation_model(corg)
model$best_family
model$all_fits
} # }