pc_cccsim-methods: A method to simulate nonstationary high-dimensional CCC GARCH...

In segMGarch: Multiple Change-Point Detection for High-Dimensional GARCH Processes

Description

A S4 method that takes as an input a simMGarch object and outputs a simulated nonstationary CCC model. The formulation of the of the piecewise constant CCC model is given in the simMGarch class.

Usage

pc_cccsim(object)

## S4 method for signature 'simMGarch'
pc_cccsim(object)

Arguments

object

a simMGarch object

References

Cho, Haeran, and Karolos Korkas. "High-dimensional GARCH process segmentation with an application to Value-at-Risk." arXiv preprint arXiv:1706.01155 (2018).

Examples

pw.CCC.obj <- new("simMGarch")
pw.CCC.obj <- pc_cccsim(pw.CCC.obj)
par(mfrow=c(1,2))
ts.plot(pw.CCC.obj@y[1,],main="a single simulated time series",ylab="series")
ts.plot(pw.CCC.obj@h[1,],main="a single simulated conditional variance",ylab="variance")

segMGarch documentation built on May 2, 2019, 7:23 a.m.