RAC: Robinson's Agreement Coefficient (RAC).

In metrica: Prediction Performance Metrics

Robinson's Agreement Coefficient (RAC).

Description

It estimates the agreement coefficient suggested by Robinson (1957; 1959) for a continuous predicted-observed dataset.

Usage

RAC(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 RAC measures both accuracy and precision (general agreement). It is normalized, dimensionless, bounded (0 to 1), and symmetric (invariant to predicted-observed orientation). 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

Robinson (1957). The statistical measurement of agreement. Am. Sociol. Rev. 22(1), 17-25 \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/2088760")}

Robinson (1959). The geometric interpretation of agreement. Am. Sociol. Rev. 24(3), 338-345 \Sexpr[results=rd]{tools:::Rd_expr_doi("10.2307/2089382")}

Examples

set.seed(1)
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- X + rnorm(n=100, mean = 0, sd = 3)
RAC(obs = X, pred = Y)

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