sim_parCoef: Generate a periodic autoregression model

In GeoBosh/pcts: Periodically Correlated and Periodically Integrated Time Series

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

\insertRef

boshnakov2009genpcts

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))

GeoBosh/pcts documentation built on Dec. 8, 2023, 9:57 p.m.