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Inter-Quartile Root Mean Squared Error

Source: R/reg_iqRMSE.R
iqRMSE.Rd

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.

Value

an object of class numeric within a list (if tidy = FALSE) or within a data frame (if tidy = 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

Examples

# \donttest{
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)
#> $iqRMSE
#> [1] 0.2413148
#> 
# }