Description Usage Arguments Value Author(s)
Method for performing rolling estimation of the GO-GARCH model.
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spec |
A GO-GARCH spec object of class |
data |
A multivariate data object. Can be a matrix or data.frame or timeSeries. |
n.ahead |
The forecast horizon (only 1-ahead supported for rolling forecasts). |
forecast.length |
The length of the total forecast for which out of sample data from the dataset will be excluded for testing. |
n.start |
Instead of forecast.length, this determines the starting point in the dataset from which to initialize the rolling forecast. |
refit.every |
Determines every how many periods the model is re-estimated. |
refit.window |
Whether the refit is done on an expanding window including all the previous data or a moving window where all previous data is used for the first estimation and then moved by a length equal to refit.every (unless the window.size option is used instead). |
window.size |
If not NULL, determines the size of the moving window in the rolling estimation, which also determines the first point used. |
solver |
The solver to use. |
fit.control |
Control parameters parameters passed to the fitting function. |
solver.control |
Control parameters passed to the solver. |
rseed |
Initialization seed for first ICA fit. The rest of the ICA fits are initialized with the previous mixing matrix (using A.init). |
cluster |
A cluster object created by calling |
save.fit |
Whether to save the fitted objects of class |
save.wdir |
If “save.fit” is true, the directory in which to save the
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An object of class goGARCHroll
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Alexios Galanos
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