Erel function

Relative Model Efficiency (Erel)

It estimates the Erel model efficiency using differences to observations.

Erel(data = NULL, obs, pred, tidy = FALSE, na.rm = TRUE)

Arguments

• data: (Optional) argument to call an existing data frame containing the data.
• obs: Vector with observed values (numeric).
• pred: Vector with predicted values (numeric).
• tidy: Logical operator (TRUE/FALSE) to decide the type of return. TRUE returns a data.frame, FALSE returns a list; Default : FALSE.
• na.rm: Logic argument to remove rows with missing values (NA). Default is na.rm = TRUE.

Returns

an object of class numeric within a list (if tidy = FALSE) or within a data frame (if tidy = TRUE).

Details

The Erel model efficiency normalizes both residuals (numerator) and observed deviations (denominator) by observed values before squaring them. Compared to the NSE, the Erel is suggested as more sensitive to systematic over- or under-predictions. For the formula and more details, see online-documentation

Examples

set.seed(1)
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- rnorm(n = 100, mean = 0, sd = 9)
Erel(obs = X, pred = Y)

References

Krause et al. (2005). Comparison of different efficiency criteria for hydrological model assessment. Adv. Geosci. 5, 89–97. tools:::Rd_expr_doi("10.5194/adgeo-5-89-2005")