E1 {metrica} | R Documentation |
Absolute Model Efficiency (E1)
Description
It estimates the E1 model efficiency using absolute differences.
Usage
E1(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. |
Details
The E1 is a type of model efficiency that modifies the Nash-Sutcliffe model efficiency by using absolute residuals instead of squared residuals. The E1 is used to overcome the NSE over-sensitivity to extreme values caused by the used of squared residuals. For the formula and more details, see online-documentation
Value
an object of class numeric
within a list
(if tidy = FALSE) or within a
data frame
(if tidy = TRUE).
References
Legates & McCabe (1999). Evaluating the use of “goodness-of-fit” measures in hydrologic and hydroclimatic model validation. Water Resour. Res. doi:10.1029/1998WR900018
Examples
set.seed(1)
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- rnorm(n = 100, mean = 0, sd = 9)
E1(obs = X, pred = Y)