跳跃采样:频域中的子抽样

Skip sampling: subsampling in the frequency domain

Biometrika · 2024
被引 0
ABS 4

中文导读

提出一种对离散傅里叶变换坐标进行子抽样的新方法,理论性质良好,在线性谱均值和比率统计上表现与频域自助法相当,但计算更省、数值更稳定。

Abstract

Summary Over the last 35 years, several bootstrap methods for time series have been proposed. Popular time domain methods include the block bootstrap, the stationary bootstrap, the linear process bootstrap, among others; subsampling for time series is also available, and is closely related to the block bootstrap. The frequency domain bootstrap has been performed either by resampling the periodogram ordinates or by resampling the ordinates of the discrete Fourier transform. The paper at hand proposes a novel construction of subsampling the discrete Fourier transform ordinates, and investigates its theoretical properties and realm of applicability. Numerical studies show that the new method performs comparably to the frequency domain bootstrap for linear spectral means and ratio statistics, while at the same time yielding significant computational savings as well as numerical stability. Some key words: Discrete Fourier transform; Spectral density, Time series.

时间序列频域分析自助法子抽样离散傅里叶变换