RMAE: Relative Mean Absolute Error (RMAE)

In metrica: Prediction Performance Metrics

Relative Mean Absolute Error (RMAE)

Description

It estimates the RMAE for a continuous predicted-observed dataset.

Usage

RMAE(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 RMAE normalizes the Mean Absolute Error (MAE) by the mean of observations. The closer to zero the lower the prediction error. 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).

Examples

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

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