smooth.periodogram: Smoothing periodogram In LSTS: Locally Stationary Time Series

Description

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

Usage

 `1` ```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].

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`). λ 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`.

Value

A list with with the smooth periodogram and the lambda values

`smooth.spline`, `periodogram`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```# 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") ```