funRMSE: Calculate the RMSE, MSE, MAE, and WAE Rounded to 4 digits

In NNbenchmark: Datasets and Functions to Benchmark Neural Network Packages

Description

Calculate the Root Mean Squared Error (RMSE), the Mean Squared Error (MSE), the Mean Absoluter Error (MAE), and the Worst Absolute Error (WAE). The result is rounded to 4 digits by default. Apply na.rm = TRUE

Usage

funRMSE(y_pred, y0, dgts = 4)

funMSE(y_pred, y0, dgts = 4)

funMAE(y_pred, y0, dgts = 4)

funWAE(y_pred, y0, dgts = 4)

Arguments

y_pred	numeric vector of the predicted values
y0	numeric vector of the observed values
dgts	integer value for how many digits to round to

Value

A numeric value, either the RMSE, MSE, MAE, or WAE.

Examples

y0 <- 1:19
y_pred <- y0 + rnorm(length(y0), sd = 0.3)
funRMSE(y_pred, y0)
funMSE( y_pred, y0)
funMAE( y_pred, y0)
funWAE( y_pred, y0)

NNbenchmark documentation built on June 5, 2021, 5:06 p.m.