boot_wild {boodd} | R Documentation |
TFT wild bootstrap.
Description
The wild bootstrap is used to bootstrap the Fourier coefficients for the Time Frequency Toggle (TFT)-Bootstrap (see Kirch and Politis (2011)).
Usage
boot_wild(X, n = length(X), h, kernel, t)
Arguments
X |
A numeric vector representing a time series. |
n |
An integer; by default is the length of time series |
h |
A positive numeric value specifying the bandwidth used to compute the kernel estimator
in case of local bootstrap.
By default it is equal to |
kernel |
An integer value indicating the kernel type. Use |
t |
An integer indicating the number of bootstrap replications. |
Details
The function centers process X
by subtracting its mean,
then computes the Fourier coefficients using
the Fast Fourier Transform (FFT). These coefficients are used to compute periodograms, which
are then smoothed using a spectral density estimation method based on the chosen
kernel kernel
and bandwidth h
.
Random normal samples are scaled by these smoothed spectral densities to generate
bootstrapped replicates.
Value
A matrix where each column contains a bootstrap replicate of the time series X
.
Author(s)
We are grateful to Claudia Kirch for providing the original code in R
.
References
Bertail, P. and Dudek, A. (2025). Bootstrap for Dependent Data, with an R package (by Bernard Desgraupes and Karolina Marek) - submitted.
Kirch, C. and Politis, D. N. (2011). TFT-Bootstrap: Resampling time series in the frequency domain to obtain replicates in the time domain, Annals of Statistics, vol.
See Also
tft_boot
, boot_res
,
boot_local
.
Examples
# see the mother function tft_boot