Periodograms and Spectral Estimates for Rhythm Data
- 1 May 1995
- journal article
- research article
- Published by Taylor & Francis in Biological Rhythm Research
- Vol. 26 (2) , 149-172
- https://doi.org/10.1080/09291019509360333
Abstract
Periodogram analysis and spectral analysis are described and evaluated as techniques for identifying periodic components in biological time series. The discussion focusses on spectral window estimates applied to the classical (Shuster) periodogram, and on the recently popular maximum entropy methods. These are preferred to Whittaker's approach. The application and scope of the methods is illustrated through simulated examples, and some suggestions are made for practical implementation.Keywords
This publication has 14 references indexed in Scilit:
- Rhythms and autocorrelation analysisBiological Rhythm Research, 1995
- The analysis of biological time‐series data: Some preliminary considerationsBiological Rhythm Research, 1995
- Comparisons between “Periodograms” and spectral analysis: Apples are apples after allJournal of Theoretical Biology, 1991
- Comparisons between periodograms and spectral analysis: Don't expect apples to taste like orangesJournal of Theoretical Biology, 1990
- The search for hidden periodicities in biological time series revisitedJournal of Theoretical Biology, 1989
- Further Evidence that the Circadian Clock in Drosophila is a Population of Coupled Ultradian OscillatorsJournal of Biological Rhythms, 1987
- Circadian and ultradian rhythms inperiod mutants ofDrosophila melanogasterBehavior Genetics, 1987
- A Study of Autoregressive and Window Spectral EstimationJournal of the Royal Statistical Society Series C: Applied Statistics, 1981
- The asymptotic distribution of the Whittaker periodogram and a related chi-squared statistic for stationary processesBiometrika, 1974
- The search for rhythmicity in biological time-seriesJournal of Theoretical Biology, 1965