ACVS: Autocovariance sequence
In sapa: Spectral Analysis for Physical Applications

Description Usage Arguments Value See Also Examples

Calculates the autocovariance sequence for an input time series.

1	ACVS(x, biased=TRUE, center=TRUE)

`x`	a numeric vector representing a uniformly sampled real-valued time series.
`biased`	a logical value. If `TRUE`, the biased estimator (normalized by N, the number of samples in the time series) is returned. If `FALSE`, the result is the unbiased estimator (the kth ACVS value is normalized by N - \|k\| for the unbiased case where k=0,...,N-1). Default: `TRUE`.
`center`	a logical value. If `TRUE`, the series is first centered (sample mean is subtracted from series) prior to calculating the ACVS. Default: `TRUE`.

a numeric vector containing the single-sided ACVS for lags k=0,...,N-1 where N is the length of the input time series.

SDF.

## calculate the ACVS for an N(0,1) realization 
plot(seq(0,99), ACVS(rnorm(100)), type="l", lwd=2,
    xlab="lag",ylab="ACVS(rnorm(100))")
gridOverlay()