qspec.lw: Lag-Window (LW) Estimator of Quantile Spectrum

In qfa: Quantile-Frequency Analysis (QFA) of Time Series

Lag-Window (LW) Estimator of Quantile Spectrum

Description

This function computes lag-window (LW) estimate of quantile spectrum with or without quantile smoothing from time series or quantile autocovariance function (QACF).

Usage

qspec.lw(
  y,
  tau,
  y.qacf = NULL,
  M = NULL,
  method = c("none", "gamm", "sp"),
  spar = "GCV",
  n.cores = 1,
  cl = NULL
)

Arguments

y	vector or matrix of time series (if matrix, nrow(y) = length of time series)
tau	sequence of quantile levels in (0,1)
y.qacf	matrix or array of pre-calculated QACF (default = NULL: compute from y and tau); if y.qacf is supplied, y and tau can be left unspecified
M	bandwidth parameter of lag window (default = NULL: quantile periodogram)
method	quantile smoothing method: "gamm" for mgcv::gamm(), "sp" for stats::smooth.spline(), or "none" (default)
spar	smoothing parameter in smooth.spline() if method = "sp" (default = "GCV")
n.cores	number of cores for parallel computing (default = 1)
cl	pre-existing cluster for repeated parallel computing (default = NULL)

Value

A list with the following elements:

spec	matrix or array of spectral estimate
spec.lw	matrix or array of spectral estimate without quantile smoothing
lw	lag-window sequence
qacf	matrix or array of quantile autocovariance function if y.qacf = NULL

Examples

y1 <- stats::arima.sim(list(order=c(1,0,0), ar=0.5), n=64)
y2 <- stats::arima.sim(list(order=c(1,0,0), ar=-0.5), n=64)
tau <- seq(0.1,0.9,0.05)
n <- length(y1)
ff <- c(0:(n-1))/n
sel.f <- which(ff > 0 & ff < 0.5)
y.qacf <- qacf(cbind(y1,y2),tau)
y.qper.lw <- qspec.lw(y.qacf=y.qacf,M=5)$spec
qfa.plot(ff[sel.f],tau,Re(y.qper.lw[1,1,sel.f,]))
y.qper.lwqs <- qspec.lw(y.qacf=y.qacf,M=5,method="sp",spar=0.9)$spec
qfa.plot(ff[sel.f],tau,Re(y.qper.lwqs[1,1,sel.f,]))

qfa documentation built on April 11, 2025, 5:49 p.m.