Description Usage Arguments Value Author(s) References See Also Examples
CVar
computes the errors obtained by applying an autoregressive modelling function to subsets of the time series y
using k-fold cross-validation as described in Bergmeir, Hyndman and Koo (2015).
1 |
y |
Univariate time series |
k |
Number of folds to use for cross-validation. |
FUN |
Function to fit an autoregressive model. Currently, it only works with the |
cvtrace |
Provide progress information. |
... |
Other arguments are passed to |
A list containing information about the model and accuracy for each fold, plus other summary information computed across folds.
Gabriel Caceres and Rob J Hyndman
Bergmeir, C., Hyndman, R.J., Koo, B. (2015) A note on the validity of cross-validation for evaluating time series prediction. Monash working paper 10/15. http://robjhyndman.com/working-papers/cv-time-series/.
CV, tsCV.
1 2 3 |
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