Skip to contents

Negated CRPS for empirical predictive distributions

Source: R/scores.R
crps_empirical.Rd

Wrapper over scoringRules::crps_sample using method = "edf" (empirical distribution function, O(n log n) via quantile decomposition of Laio & Tamea, 2007). Positively oriented: higher = better.

Usage

crps_empirical(ensemble, y)

Arguments

ensemble

Matrix. T x n matrix of forecast draws. Each row corresponds to one observation in y and comprises n simulation draws from the predictive distribution. For Historical Simulation: each row is the past WINDOW returns.

y

Numeric vector of length T. Realised observations.

Value

Numeric vector of length T of CRPS values in (-Inf, 0] (negated loss).

Details

Requires nrow(ensemble) == length(y). Passes dat = ensemble directly to crps_sample which handles vectorisation over rows natively. show_messages is suppressed as the "edf" method requires no bandwidth selection messages.

Examples

if (requireNamespace("scoringRules", quietly = TRUE)) {
  ensemble <- matrix(c(0.1, 0.2, 0.3, 1.0, 1.1, 1.2), nrow = 2, byrow = TRUE)
  crps_empirical(ensemble, y = c(0.25, 1.05))
}
#> [1] -0.03888889 -0.03888889