E1: Absolute Model Efficiency (E1)

In metrica: Prediction Performance Metrics

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. \Sexpr[results=rd]{tools:::Rd_expr_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)

metrica documentation built on June 30, 2024, 5:07 p.m.