pc_Sigma {segMGarch} | R Documentation |
An S4 method that takes a simMGarch
object and outputs simulated correlated time series with a piecewise constant covariance matrix.
The correlations are generated as σ_{i, i'} = ρ^{|i-i'|} with ρ taking values from (-1,1). The exact variables that will contain a change-point are
randomly selected and controlled by r
in the simMGarch
object.
pc_Sigma(object) ## S4 method for signature 'simMGarch' pc_Sigma(object)
object |
A |
Cho, Haeran, and Karolos Korkas. "High-dimensional GARCH process segmentation with an application to Value-at-Risk." arXiv preprint arXiv:1706.01155 (2017).
cp=500 n=2000 pw.CCC.obj <- new("simMGarch") pw.CCC.obj@changepoints=cp pw.CCC.obj@n=n pc_Sigma.obj <- pc_Sigma(pw.CCC.obj) par(mfrow=c(1,2)) #requires corrplot library #correlation matrix before the changepoint #corrplot::corrplot.mixed(cor(pc_Sigma.obj@cor_errors[1:cp,]), order="hclust", tl.col="black") #correlation matrix after the changepoint #corrplot::corrplot.mixed(cor(pc_Sigma.obj@cor_errors[(cp+1):n,]), order="hclust", tl.col="black")