Give partial periodic autocorrelations or other partial prediction quantities for a pcAcvf object.

Usage

alg1util(x, s, at0 = 1)

Arguments

x: an object of a class inheriting from pc.Model.WeaklyStat
s: the required quantity, the name of one of the elements of the list returned by alg1.
at0: if not identical to "var", replace the elements of the result at lag zero with 1, see `Details'.

Details

This function is a wrapper for alg1(). It calls alg1, to do the computations and returns the requested element as an object from class slMatrix. The model order is set to the maximal lag avialable in x,

If at0 is the character string "var", then the lag zero values in the result are set to the lag zero autocovariances, otherwise they are set to 1. This is mainly relevant for the periodic partial autocorrelations (s="be"), since the setting at0="var" ensures that they are in one to one correspondence with the autocovariances.

Value

the requested quantity as an object of type slMatrix

References

Lambert-Lacroix S (2000). ``On periodic autoregressive process estimation .'' IEEE Transactions on Signal Processing, 48( 6 ), pp. 1800-1803.

Lambert-Lacroix S (2005). `` Extension of autocovariance coefficients sequence for periodically correlated processes.'' Journal of Time Series Analysis, 26(6), pp. 423-435.

Author

Georgi N. Boshnakov

Examples

r1 <- rbind(c(1,0.81,0.729),c(1,0.90,0.900))

# example of Lambert-Lacroix
data(ex1f)
pc3 <- slMatrix(period=2,maxlag=5,f=ex1f,type="tt")
res0p2 <- alg1(pc3[],c(0,2))
res1p2 <- alg1(pc3[],c(1,2))
res3p3 <- alg1(pc3[],c(3,3))