Nonparametric functionals of spectral distributions and their applications to time series analysis

Tze Leung Lai; Haipeng Xing

doi:10.1016/j.jspi.2006.06.025

Nonparametric functionals of spectral distributions and their applications to time series analysis

Tze Leung Lai
, Haipeng Xing

Applied Mathematics and Statistics

Stony Brook University

Stanford University

Research output: Contribution to journal › Article › peer-review

Abstract

There is a close analogy between empirical distributions of i.i.d. random variables and normalized spectral distributions of wide-sense stationary processes. Herein we make use of this analogy to develop nonparametric comparisons of two spectral distributions and nonparametric tests of stationarity versus change-point alternatives via spectral analysis of a time series.

Original language	English
Pages (from-to)	1066-1075
Number of pages	10
Journal	Journal of Statistical Planning and Inference
Volume	137
Issue number	3
DOIs	https://doi.org/10.1016/j.jspi.2006.06.025
State	Published - Mar 1 2007

Keywords

Change point
Frequency domain
Linear process
Weak convergence

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10.1016/j.jspi.2006.06.025

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title = "Nonparametric functionals of spectral distributions and their applications to time series analysis",

abstract = "There is a close analogy between empirical distributions of i.i.d. random variables and normalized spectral distributions of wide-sense stationary processes. Herein we make use of this analogy to develop nonparametric comparisons of two spectral distributions and nonparametric tests of stationarity versus change-point alternatives via spectral analysis of a time series.",

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author = "Lai, \{Tze Leung\} and Haipeng Xing",

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T1 - Nonparametric functionals of spectral distributions and their applications to time series analysis

AU - Lai, Tze Leung

AU - Xing, Haipeng

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N2 - There is a close analogy between empirical distributions of i.i.d. random variables and normalized spectral distributions of wide-sense stationary processes. Herein we make use of this analogy to develop nonparametric comparisons of two spectral distributions and nonparametric tests of stationarity versus change-point alternatives via spectral analysis of a time series.

AB - There is a close analogy between empirical distributions of i.i.d. random variables and normalized spectral distributions of wide-sense stationary processes. Herein we make use of this analogy to develop nonparametric comparisons of two spectral distributions and nonparametric tests of stationarity versus change-point alternatives via spectral analysis of a time series.

KW - Change point

KW - Frequency domain

KW - Linear process

KW - Weak convergence

UR - https://www.scopus.com/pages/publications/33750526934

U2 - 10.1016/j.jspi.2006.06.025

DO - 10.1016/j.jspi.2006.06.025

M3 - Article

SN - 0378-3758

VL - 137

SP - 1066

EP - 1075

JO - Journal of Statistical Planning and Inference

JF - Journal of Statistical Planning and Inference

IS - 3

ER -

Nonparametric functionals of spectral distributions and their applications to time series analysis

Abstract

Keywords

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