Abstract
This paper contains some preliminary results from an analysis of the sensitivity of Classical, Bayesian and Maximum Entropy Spectrum analysis to detrending procedures. The findings suggest that their performance in discovering periodicities in nonstationary series is affected by the assumption made about the trend. A combination of the three methods when trends are not simple functions of time is desirable and necessary to obtain precise information about the periodic behavior of the data analysed.
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© 1989 Springer Science+Business Media Dordrecht
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Sanchez, J. (1989). Application of Classical, Bayesian and Maximum Entropy Spectrum Analysis to Nonstationary Time Series Data. In: Skilling, J. (eds) Maximum Entropy and Bayesian Methods. Fundamental Theories of Physics, vol 36. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-7860-8_31
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DOI: https://doi.org/10.1007/978-94-015-7860-8_31
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-4044-2
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