Description Usage Arguments Value Author(s) References
Calculates correlation for crossvalidation
1 |
Y |
Time series |
PredInterval |
Prediction interval, i.e. 1 represents predicting one observation ahead |
Nembed |
Embedding dimension (if using simplex) |
Theta |
Magnitude of non-linearity (if using S-map) |
Method |
Method to use, either 'Smap' or 'Simplex' |
Returns a table comparing crossvalidation predictions and observations, as well as the their correlation
James Thorson
Sugihara, G., and May, R.M. 1990. Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series. Nature 334: 734-741. Sugihara, G. 1994. Nonlinear forecasting for the classification of natural time series. Philosophical Transactions of the Royal Society B: Biological Sciences 348: 477-495.
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