| KGE {metrica} | R Documentation |
Kling-Gupta Model Efficiency (KGE).
Description
It estimates the KGE for a predicted-observed dataset.
Usage
KGE(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 KGE is a normalized, dimensionless, model efficiency that measures general agreement. It presents accuracy, precision, and consistency components. It is symmetric (invariant to predicted observed orientation). It is positively bounded up to 1. The closer to 1 the better. 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
Kling et al. (2012). Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios. Journal of Hydrology 424-425, 264-277. doi:10.1016/j.jhydrol.2012.01.011
Examples
set.seed(1)
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- rnorm(n = 100, mean = 0, sd = 9)
KGE(obs = X, pred = Y)