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 X but allow for a smaller sample size m to perform moon bootstrap.

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 n^{-2/3}.

kernel

An integer value indicating the kernel type. Use 0 for the Daniell kernel or any other value for the Bartlett-Priestley (Epanechnikov) kernel (by default).

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

[Package boodd version 0.1 Index]