mae: Mean Absolute Error

In gencve: General Cross Validation Engine

Description

This is a widely used criterion since the time of Laplace. Just as least-squares is optimal for mean-square error loss functions, least absolute deviation is optimal for mean absolute error loss functions. See Wikipedia article https://en.wikipedia.org/wiki/Mean_absolute_error.

Usage

mae(yTest, yHat)

Arguments

yTest	test data
yHat	predictions of the test data

Details

tba

Value

mean percentage absolute errors

Author(s)

A. I. McLeod

See Also

gcv, mse, mape, smape

Examples

mape(abs(rnorm(10)), rep(sqrt(2/pi),10))

Example output

[1] 122.5959

gencve documentation built on May 2, 2019, 6:08 a.m.