LSTS (version 2.1)

smooth.periodogram: Smoothing periodogram

Description

This function returns the smoothing periodogram of a stationary time serie, its plot and its Fourier frequency.

Usage

smooth.periodogram(y, plot = TRUE, spar = 0)

Arguments

y

(type: numeric) data vector.

plot

(type: logical) logical argument which allows to plot the periodogram. Defaults to TRUE.

spar

(type: numeric) smoothing parameter, typically (but not necessarily) in \((0,1].\)

Value

A list with with the smooth periodogram and the lambda values

Details

smooth.periodogram computes the periodogram from y vector and then smooth it with smoothing spline method, which basically approximates a curve using a cubic spline (see more details in smooth.spline). \(\lambda\) is the Fourier frequency obtained through periodogram. It must have caution with the minimum length of y, because smooth.spline requires the entered vector has at least length 4 and the length of y does not equal to the length of the data of the periodogram that smooth.spline receives. If it presents problems with tol (tolerance), see smooth.spline.

See Also

smooth.spline, periodogram

Examples

# NOT RUN {
# AR(1) simulated
require(ggplot2)
set.seed(1776)
ts.sim <- arima.sim(n = 1000, model = list(order = c(1, 0, 0), ar = 0.7))
per <- periodogram(ts.sim)
aux <- smooth.periodogram(ts.sim, plot = FALSE, spar = .7)
sm_p <- data.frame(x = aux$lambda, y = aux$smooth.periodogram)
sp_d <- data.frame(
  x = aux$lambda,
  y = spectral.density(ar = 0.7, lambda = aux$lambda)
)
g <- per$plot
g +
  geom_line(data = sm_p, aes(x, y), color = "#ff7f0e") +
  geom_line(data = sp_d, aes(x, y), color = "#d31244")
# }