Simulate hazard scenarios via Karhunen-Loève Expansion

Generates n_scenarios synthetic hazard fields from the KLE of the fitted covariance model, following Eq. 8–11 of Clavijo Mesa et al. (2026, SF paper): build \(\bar{C}\), eigen-decompose and truncate to var_retain variance, sample KLE coefficients, back-transform via \(\Phi\) and the inverse marginal CDFs.

Usage

hm_simulate_sf_kle(
  corrmodel,
  D,
  fits,
  n_scenarios = 1000L,
  var_retain = 0.95,
  seed = NULL
)

Arguments

corrmodel

An hm_corrmodel from [hm_fit_correlation_model()].

D

Symmetric distance matrix in km from [hm_distance_matrix()]. Must have nrow(fits) rows.

fits

data.frame from [hm_fit_marginals()] for the same land cells.

n_scenarios

Number of synthetic scenarios. Defaults to 1000.

var_retain

Variance fraction retained in KLE truncation. Defaults to 0.95.

seed

Optional integer random seed.

Value

A numeric matrix (\(S \times N\)) of simulated hazard intensities. Attributes family, k_modes, var_retain, and var_explained are attached.

References

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

See also

[hm_fit_correlation_model()], [hm_fit_marginals()]

Examples

if (FALSE) { # \dontrun{
model     <- hm_fit_correlation_model(corg)
scenarios <- hm_simulate_sf_kle(model, D, fits,
                                 n_scenarios = 1000, seed = 42)
attr(scenarios, "k_modes")
attr(scenarios, "var_explained")
} # }