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Forecast accuracy metrics for load curves

Source: R/metrics.R
elcf4r_metrics.Rd

Compute NMAE, NRMSE, sMAPE and MASE between observed and predicted load curves, as in the posters.

Usage

elcf4r_metrics(truth, pred, seasonal_period = NULL, naive_pred = NULL)

Arguments

truth

Numeric vector or matrix of observed values.

pred

Numeric vector or matrix of predicted values, same shape.

seasonal_period

Seasonal period for the naive benchmark in the MASE denominator (for daily curves with half hourly sampling, a value of 48 is appropriate).

naive_pred

Optional numeric vector or matrix of naive benchmark predictions with the same shape as truth. When supplied, MASE is computed against this explicit naive forecast instead of inferring the denominator from seasonal_period within truth.

Value

A named list with elements nmae, nrmse, smape, mase.