iqRMSE: Inter-Quartile Root Mean Squared Error

In metrica: Prediction Performance Metrics

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)

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