metrica (version 2.1.0)

Erel: Relative Model Efficiency (Erel)

Description

It estimates the Erel model efficiency using differences to observations.

Usage

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

Value

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

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

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")

Examples

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