acf.M {dse1}R Documentation

Calculate Auto-Covariance

Description

Calculate a matrix with partitions [M0|...|Mi|...|Ml] giving the auto-covariance.

Usage

    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, ...)

Arguments

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.

Value

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).

Examples

    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