ucarima_wk: Wiener Kolmogorov Estimators

In palatej/rjd3toolkit: Utility Functions around 'JDemetra+ 3.0'

Wiener Kolmogorov Estimators

Description

Wiener Kolmogorov Estimators

Usage

ucarima_wk(ucm, cmp, signal = TRUE, nspectrum = 601, nwk = 300)

Arguments

ucm	An UCARIMA model returned by ucarima_model().
cmp	Index of the component for which we want to compute the filter
signal	TRUE for the signal (component), FALSE for the noise (complement)
nspectrum	Number of points used to compute the (pseudo-) spectrum of the estimator
nwk	Number of weights of the Wiener-Kolmogorov filter returned in the result

Value

A list with the (pseudo-)spectrum, the weights of the filter and the squared-gain function (with the same number of points as the spectrum)

Examples

mod1 <- arima_model("trend", delta = c(1, -2, 1))
mod2 <- arima_model("noise", var = 1600)
hp <- ucarima_model(components = list(mod1, mod2))
wk1 <- ucarima_wk(hp, 1, nwk = 50)
wk2 <- ucarima_wk(hp, 2)
plot(wk1$filter, type = "h")

palatej/rjd3toolkit documentation built on Oct. 30, 2024, 10:46 p.m.