sim_parCoef {pcts}

Generate a periodic autoregression model

Description

Generate a periodic autoregression model, possibly integrated.

Usage

sim_parCoef(period, n.root, sigma2 = rep(1, period), ...)

Arguments

period

number of seasons in a cycle.

n.root

number of non-zero roots, see details.

sigma2

variances of the innovations.

...

additional arguments to be passed down to sim_pcfilter

Details

sim_parCoef uses the multi-companion method to generate the model. The function is essentially a wrapper for sim_pcfilter.

The order of the filter is set to n.root for each season. Part of the spectral information may be specified with the "..." arguments, see sim_pcfilter and sim_mc for a discussion of this.

Value

a periodic autoregression model as a list with elements:

ar

a matrix whose ith row contains the coefficients for the iseason,

sigma2

the innovation variances, a numeric vector.

Author(s)

Georgi N. Boshnakov

References

Boshnakov GN, Iqelan BM (2009). “Generation of time series models with given spectral properties.” J. Time Series Anal., 30(3), 349–368. ISSN 0143-9782, doi:10.1111/j.1467-9892.2009.00617.x.

See Also

sim_pcfilter

Examples

sim_parCoef(2, 4)                    # 2 seasons
sim_parCoef(2, 4, sigma2 = c(2, 4))
sim_parCoef(2, 1)
sim_parCoef(4, 2)                    # 4 seasons

sim_parCoef(period = 4, n.root = 6,
    eigabs = c(1, 1, 1, 0.036568887, 0.001968887),
    type.eigval = c("cp", "r", "r", "r",  "r"),
    eigsign     = c(pi/2,   1,  -1,   1,   -1))