tvspc: Evolutionary Power Spectra by Time Varying AR Model

In TSSS: Time Series Analysis with State Space Model

Evolutionary Power Spectra by Time Varying AR Model

Description

Estimate evolutionary power spectra by time varying AR model.

Usage

tvspc(arcoef, sigma2, var = NULL, span = 20, nf = 200)

Arguments

arcoef	time varying AR coefficients.
sigma2	variance of the observational noise.
var	time varying variance.
span	local stationary span.
nf	number of frequencies in evaluating power spectrum.

Value

return an object of class "tvspc" giving power spectra, which has a plot method (plot.tvspc).

References

Kitagawa, G. (2020) Introduction to Time Series Modeling with Applications in R. Chapman & Hall/CRC.

Kitagawa, G. and Gersch, W. (1996) Smoothness Priors Analysis of Time Series. Lecture Notes in Statistics, No.116, Springer-Verlag.

Kitagawa, G. and Gersch, W. (1985) A smoothness priors time varying AR coefficient modeling of nonstationary time series. IEEE trans. on Automatic Control, AC-30, 48-56.

Examples

# seismic data
data(MYE1F)
z <- tvar(MYE1F, trend.order = 2, ar.order = 8, span = 20,
          outlier = c(630, 1026), tau2.ini = 6.6e-06, delta = 1.0e-06)
spec <- tvspc(z$arcoef, z$sigma2)
plot(spec)

TSSS documentation built on Sept. 29, 2023, 9:07 a.m.