acf.M {dse1} | R Documentation |
Calculate a matrix with partitions [M0|...|Mi|...|Ml] giving the auto-covariance.
acf.M(obj, ...) acf.M(obj, lag=round(6*log(periods(obj))), type ="covariance", sub.mean=T) acf.M(obj, lag=NULL, type ="covariance", Psi=NULL) acf.M(obj, ...)
object |
An object of class TSdata or TSmodel. |
type |
With the defaults the blocks are auto-covariances. If type == 'correlation' the result is scaled to give autocorrelations. |
sub.means |
Only valid if object is of class TSdata. If F then means are not subtracted. |
Psi |
A matrix of innovation covariance. Only valid if object is of class TSmodel. |
A matrix with partitions [M0|...|Mi|...|Ml] giving the covariance or correlation, including the that between the output and input series (as in the first block row of a Hankel matrix).
if(is.R()) data("eg1.DSE.data.diff", package="dse1") z <- acf.M(eg1.DSE.data.diff) model <- TSmodel(to.SS(est.VARX.ls(eg1.DSE.data.diff))) # z <- acf.M(model) not working