Usage
gogarchsim(fit, n.sim = 1, n.start = 0, m.sim = 1,
startMethod = c("unconditional", "sample"), prereturns = NA, preresiduals = NA,
presigma = NA, mexsimdata = NULL, rseed = NULL, cluster = NULL, ...)Arguments
fit
A GO-GARCH fit object of class goGARCHfit.
n.sim
The simulation horizon.
n.start
The burn-in sample.
m.sim
The number of simulations.
startMethod
Starting values for the simulation. Valid methods are unconditional
for the expected values given the density, and sample for the
ending values of the actual data from the fit object.
prereturns
Allows the starting return data to be provided by the user.
preresiduals
Allows the starting factor residuals to be provided by the user.
presigma
Allows the starting conditional factor sigma to be provided by the user.
mexsimdata
A list of matrices with the simulated lagged external variables (if any). The
list should be of size m.sim and the matrices each have n.sim + n.start rows.
rseed
Optional seeding value(s) for the random number generator.
cluster
A cluster object created by calling makeCluster from
the parallel package. If it is not NULL, then this will be used for parallel
estimation (remember to stop the cluster on completion).