multifit-methods {rugarch} | R Documentation |
Method for multiple fitting a variety of univariate GARCH and ARFIMA models.
multifit(multispec, data, out.sample = 0, solver = "solnp", solver.control = list(), fit.control = list(stationarity = 1, fixed.se = 0, scale = 0), parallel = FALSE, parallel.control = list(pkg = c("multicore", "snowfall"), cores = 2), ...)
multispec |
A multiple GARCH or ARFIMA spec object of class |
out.sample |
A positive integer indicating the number of periods before the last to keep for out of sample forecasting (see details). |
data |
A multivariate data object. Can be a matrix or data.frame object, no other class supported at present. |
solver |
One of either “nlminb” or “solnp”. |
solver.control |
Control arguments list passed to optimizer. |
fit.control |
Control arguments passed to the fitting routine. Stationarity (only for the
GARCH case) explicitly imposes the variance stationarity constraint during
optimization. The fixed.se argument controls whether standard errors should be
calculated for those parameters which were fixed (through the fixed.pars
argument of the |
parallel |
Whether to make use of parallel processing on multicore systems. |
parallel.control |
The parallel control options including the type of package for performing the parallel calculations (‘multicore’ for non-windows O/S and ‘snowfall’ for all O/S), and the number of cores to make use of. |
... |
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A uGARCHmultifit
or ARFIMAmultifit
object containing details of the GARCH or ARFIMA fits.
Alexios Ghalanos
## Not run: data(dji30ret) spec = ugarchspec() mspec = multispec( replicate(spec, n = 4) ) fitlist = multifit(multispec = mspec, data = dji30ret[,1:4]) ## End(Not run)