A periodogram-based test for weak stationarity and consistency between sections in time series.
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.
Halliday
D M
DM
Department of Electronics, University of York, York YO105DD, UK. dh20@ohm.york.ac.uk
Rosenberg
J R
JR
Rigas
A
A
Conway
B A
BA
D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D004568:Electrodiagnosis / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D004576:Electromyography / Q000379:methods; D006801:Humans; D018482:Muscle, Skeletal / Q000502:physiology*; D015588:Observer Variation; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted; D012984:Software; D013997:Time Factors