A periodogram-based test for weak stationarity and consistency between sections in time series

D.M. Halliday, J.R. Rosenberg, A. Rigas, B.A. Conway

    Research output: Contribution to journalArticle

    8 Citations (Scopus)

    Abstract

    In one approach to spectral estimation, a sample record is broken into a number of disjoint sections, or data is collected over a number of discrete trials. Spectral parameters are formed by averaging periodograms across these discrete sections or trials. A key assumption in this approach is that of weak stationarity. This paper describes a simple test that checks if periodogram ordinates are consistent across sections as a means of assessing weak stationarity. The test is called the Periodogram Coefficient of Variation (PCOV) test, and is a frequency domain test based on a technique of spectral analysis. Application of the test is illustrated to both simulated and experimental data (EMG, physiological tremor, EEG). An additional role for the test as a useful tool in exploratory analysis of time series is highlighted.
    Original languageEnglish
    Pages (from-to)138-146
    Number of pages8
    JournalJournal of Neuroscience Methods
    Volume180
    DOIs
    Publication statusPublished - 30 May 2009

    Keywords

    • spectral analysis
    • periodogram
    • time series
    • stationarity
    • EEG
    • EMG

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