gogarchsim-methods: function: GO-GARCH Simulation
In rmgarch: Multivariate GARCH Models

Description Usage Arguments Value Author(s)

Method for simulation from a fitted GO-GARCH model.

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gogarchsim(object, 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, ...)

`object`	A GO-GARCH fit object of class `goGARCHfit` or `goGARCHfilter`.
`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).
`...`	.