gogarchsim-methods: function: GO-GARCH Simulation

In rgarch: Flexible GARCH modelling in R

Description

Method for simulation from a fitted GO-GARCH model.

Usage

gogarchsim(fit, n.sim = 1, n.start = 0, m.sim = 1, startMethod = c("unconditional", "sample"), 
		prereturns = NA, mexsimdata = NULL, rseed = NULL, parallel = FALSE, 
		parallel.control = list(pkg = c("multicore", "snowfall"), cores = 2), ...)

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.
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.
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 goGARCHsim object containing details of the GO-GARCH simulation.

Author(s)

Alexios Ghalanos

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