lambda: Duveiller's Agreement Coefficient

In metrica: Prediction Performance Metrics

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

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