{lvmisc} contains a group of useful functions to compute basic indices of accuracy. These functions can be divided in those which compute element-wise values and those which compute average values:
error()
error_abs()
error_pct()
error_abs_pct()
error_sqr()
mean_error()
mean_error_abs()
mean_error_pct()
mean_error_abs_pct()
mean_error_sqr()
mean_error_sqr_root()
bias()
loa()
You may notice that the majority of these functions have common
prefixes (error_
and mean_error_
), intended to
facilitate the use, as most text editors have an auto-complete feature.
Also all of the accuracy indices functions take actual
and
predicted
as arguments, and the functions that return
average values have na.rm = TRUE
in addition.
Let’s now see how each function computes its results
error()
It simply subtracts the predicted
from the
actual
values.
Formula: \[a_i - p_i\]
error_abs()
It returns the absolute values of the error()
function.
Formula: \[|a_i - p_i|\]
error_pct()
Divides the error by the actual
values.
Formula: \[\frac{a_i - p_i}{a_i}\cdot100\]
error_abs_pct()
Returns the absolute values of the error_pct()
function.
Formula: \[\frac{|a_i - p_i|}{|a_i|}\cdot100\]
error_sqr()
It squares the values of the error()
function.
Formula: \[(a_i - p_i)^2\]
mean_error()
It is the average of the error.
Formula: \[\frac{1}{N}\sum_{i = 1}^{N}(a_i - p_i)\]
mean_error_abs()
Computes the average of the absolute error.
Formula: \[\frac{1}{N}\sum_{i = 1}^{N}|a_i - p_i|\]
mean_error_pct()
The average of the percent error.
Formula: \[\frac{1}{N}\sum_{i = 1}^{N}\frac{a_i - p_i}{a_i}\cdot100\]
mean_error_abs_pct()
It is the average of the absolute percent error.
Formula: \[\frac{1}{N}\sum_{i = 1}^{N}\frac{|a_i - p_i|}{|a_i|}\cdot100\]
mean_error_sqr()
Averages the mean squared error.
Formula: \[\frac{1}{N}\sum_{i = 1}^{N}(a_i - p_i)^2\]
mean_error_sqr_root()
It takes the square root of the mean squared error.
Formula: \[\sqrt{\frac{1}{N}\sum_{i = 1}^{N}(a_i - p_i)^2}\]
bias()
Alias to mean_error()
.
loa()
Formula: \[bias \pm 1.96\sigma\]
Where \(\sigma\) is the standard deviation.