IntegrQuantileSD-class: Class for a simulated integrated quantile (i. e., Laplace or...

In quantspec: Quantile-Based Spectral Analysis of Time Series

Description

IntegrQuantileSD is an S4 class that implements the necessary calculations to determine an integrated version of the quantile spectral density kernel (computed via QuantileSD). In particular it can be determined for any model from which a time series of length N can be sampled via a function call ts(N).

Details

In the simulation the quantile spectral density is first determined via QuantileSD, it's values are recovered using getValues-QuantileSD and then cumulated using cumsum.

Note that, all remarks made in the documentation of the super-class QSpecQuantity apply.

Slots

qsd

a QuantileSD from which to begin the computations.

Examples

################################################################################
## This script illustrates how to estimate integrated quantile spectral densities

## Simulate a time series Y1,...,Y128 from the QAR(1) process discussed in
## Dette et. al (2015).
set.seed(2581)
Y <- ts1(128)

## For a defined set of quantile levels ... 
levels <- c(0.25,0.5,0.75)

## ... and a weight (of Type A), defined using the Epanechnikov kernel ...
wgt <- specDistrWeight()

## ... compute a smoothed quantile periodogram (based on the clipped time series).
## Repeat the estimation 100 times, using the moving blocks bootstrap with
## block length l=32.
sPG.cl <- smoothedPG(Y, levels.1 = levels, type="clipped", weight = wgt,
    type.boot = "mbb", B=100, l=32)

## Create a (model) spectral density kernel for he QAR(1) model for display
## in the next plot.
csd <- quantileSD(N=2^8, seed.init = 2581, type = "copula",
    ts = ts1, levels.1=levels, R = 100)
icsd <- integrQuantileSD(csd)

plot(sPG.cl, ptw.CIs = 0.1, qsd = icsd, type.CIs = "boot.full")

quantspec documentation built on July 15, 2020, 1:07 a.m.