tqr.fit: Trigonometric Quantile Regression (TQR)

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

Trigonometric Quantile Regression (TQR)

Description

This function computes trigonometric quantile regression (TQR) for univariate time series at a single frequency.

Usage

tqr.fit(y, f0, tau, prepared = TRUE)

Arguments

y	vector of time series
f0	frequency in [0,1)
tau	sequence of quantile levels in (0,1)
prepared	if TRUE, intercept is removed and coef of cosine is doubled when f0 = 0.5

Value

object of rq() (coefficients in $coef)

Examples

y <- stats::arima.sim(list(order=c(1,0,0), ar=0.5), n=64)
tau <- seq(0.1,0.9,0.05)
fit <- tqr.fit(y,f0=0.1,tau=tau)
plot(tau,fit$coef[1,],type='o',pch=0.75,xlab='QUANTILE LEVEL',ylab='TQR COEF')

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