MTS: SCMid – R documentation

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SCMid

Scalar Component Identification

Find the overall order of a VARMA process via the scalar component model approach

SCMid(zt, maxp = 5, maxq = 5, h = 0, crit = 0.05, output = FALSE)

`zt`	The T-by-k data matrix of a k-dimensional time series
`maxp`	Maximum AR order entertained. Default is 5.
`maxq`	Maximum MA order entertained. Default is 5.
`h`	The additional past lags used in canonical correlation analysis. Default is 0.
`crit`	Type-I error of the chi-square tests used.
`output`	A logical switch to control the output.

`Nmtx`	The table of the numbers of zero canonical correlations
`DDmtx`	The diagonal difference table of the number of zero canonical correlations

Ruey S. Tsay

Tsay (2014, Chapter 4). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

phi=matrix(c(0.2,-0.6,0.3,1.1),2,2); sigma=diag(2)
m1=VARMAsim(300,arlags=c(1),phi=phi,sigma=sigma)
zt=m1$series
m2=SCMid(zt)

All-Purpose Toolkit for Analyzing Multivariate Time Series (MTS) and Estimating Multivariate Volatility Models

v1.0

Artistic License 2.0

Authors

Ruey S. Tsay and David Wood

Initial release

2018-10-8