lambda {metrica} | R Documentation |
Duveiller's Agreement Coefficient
Description
It estimates the agreement coefficient (lambda) suggested by Duveiller et al. (2016) for a continuous predicted-observed dataset.
Usage
lambda(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
lambda measures both accuracy and precision. It is normalized, dimensionless, bounded (-1;1), and symmetric (invariant to predicted-observed orientation). lambda is equivalent to CCC when r is greater or equal to 0. The closer to 1 the better. Values towards zero indicate low correlation between observations and predictions. Negative values would indicate a negative relationship between predicted and observed. 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
Duveiller et al. (2016). Revisiting the concept of a symmetric index of agreement for continuous datasets. Sci. Rep. 6, 1-14. doi:10.1038/srep19401
Examples
set.seed(1)
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- rnorm(n = 100, mean = 0, sd = 9)
lambda(obs = X, pred = Y)