rolling_origin: Assessing forecasting accuracy with rolling origin
Description
It uses the model and the time series associated with the knnForecast
object to asses the forecasting accuracy of the model using the last
h values of the time series to build test sets applying a rolling
origin evaluation.
Usage
rolling_origin(knnf, h = NULL, rolling = TRUE)
Value
A list containing at least the following fields:
test_sets
a matrix containing the test sets used in the
evaluation. Every row contains a different test set.
predictions
The predictions for the test sets.
errors
The errors for the test sets.
global_accu
Different measures of accuracy applied to all the
errors.
h_accu
Different measures of accuracy applied to all the
errors for every forecasting horizon.
Arguments
knnf
A knnForecast object.
h
A positive integer. The forecast horizon. If NULL the
prediction horizon of the knnForecast object is used.
rolling
A logical. If TRUE (the default), forecasting
horizons from 1 to h are used. Otherwise, only horizon
h is used.
Details
This function assesses the forecast accuracy of the model used by the
knnForecast object. It uses h different test and training
sets. The first test set consists of the last h values of the time
series (the training set is formed by the previous values). The next test
set consists of the last \(h - 1\) values of the time series and so on
(the last test set is formed by the last value of the time series).