multifit-methods: function: Univariate GARCH and ARFIMA Multiple Fitting

In rgarch: Flexible GARCH modelling in R

Description

Method for multiple fitting a variety of univariate GARCH and ARFIMA models.

Usage

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), ...)

Arguments

multispec	A multiple GARCH or ARFIMA spec object of class uGARCHmultispec and ARFIMAmultispec.
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 suppored 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 ugarchspec or arfimaspec functions). The scale parameter controls whether the data should be scaled before being submitted to the optimizer.
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.
...	.

Value

A uGARCHmultifit or ARFIMAmultifit object containing details of the GARCH or ARFIMA fits.

Author(s)

Alexios Ghalanos

Examples

## Not run: 
data(dji30ret)
spec = ugarchspec()
mspec = multispec( replicate(spec, n = 4) )
fitlist = multifit(multispec = mspec, data = dji30ret[,1:4])

## End(Not run)

rgarch documentation built on May 2, 2019, 5:22 p.m.