Gaussian Approximation for Lag-Window Estimators and the Construction of Confidence Bands for the Spectral Density

IF 1.2 4区 数学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Jens-Peter Kreiß, Anne Leucht, Efstathios Paparoditis
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引用次数: 0

Abstract

In this article, we consider the construction of simultaneous confidence bands for the spectral density of a stationary time series using a Gaussian approximation for classical lag-window spectral density estimators evaluated at the set of all positive Fourier frequencies. The Gaussian approximation opens up the possibility to verify asymptotic validity of a multiplier bootstrap procedure and, even further, to derive the corresponding rate of convergence. A small simulation study sheds light on the finite sample properties of this bootstrap proposal.

滞后窗估计量的高斯近似及谱密度置信带的构造
在这篇文章中,我们考虑了一个平稳时间序列的谱密度的同时置信带的构造,使用高斯近似的经典滞后窗谱密度估计在所有正傅立叶频率的集合上进行评估。高斯近似为验证乘法器自举过程的渐近有效性提供了可能性,甚至进一步推导出相应的收敛速率。一个小型的模拟研究揭示了这个自举方案的有限样本特性。
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来源期刊
Journal of Time Series Analysis
Journal of Time Series Analysis 数学-数学跨学科应用
CiteScore
2.00
自引率
0.00%
发文量
39
审稿时长
6-12 weeks
期刊介绍: During the last 30 years Time Series Analysis has become one of the most important and widely used branches of Mathematical Statistics. Its fields of application range from neurophysiology to astrophysics and it covers such well-known areas as economic forecasting, study of biological data, control systems, signal processing and communications and vibrations engineering. The Journal of Time Series Analysis started in 1980, has since become the leading journal in its field, publishing papers on both fundamental theory and applications, as well as review papers dealing with recent advances in major areas of the subject and short communications on theoretical developments. The editorial board consists of many of the world''s leading experts in Time Series Analysis.
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