| iqRMSE {metrica} | R Documentation |
Inter-Quartile Root Mean Squared Error
Description
It estimates the IqRMSE for a continuous predicted-observed dataset.
Usage
iqRMSE(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 iqRMSE normalizes the RMSE by the length of the inter-quartile range of observations (percentiles 25th to 75th). As an error metric, the lower the values 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).
Examples
set.seed(1)
X <- rnorm(n = 100, mean = 0, sd = 10)
Y <- X + rnorm(n=100, mean = 0, sd = 3)
iqRMSE(obs = X, pred = Y)