Abstract
The statistical treatment of time-series data has a long history of theoretical development, continuing to the present. A number of modern texts are available on the topic (e.g., Cox and Lewis, 1966; Hannan, 1970; Jenkins and Watts, 1969; Kendall, 1973; Koopmans, 1974; Parzen, 1967; Rosenblatt, 1963), and no attempt will be made here to summarize such general treatments. Instead, the approach here is nonmathematical and pragmatic, with emphasis confined to those techniques and issues of interpretation that have proved to be important for research on biological rhythms whose adaptive significance involves the need for an organism to maintain an appropriate phase relationship with a regularly cyclic environment. The physiological process by which a majority of animals accomplish this objective is an endogenous, entrainable rhythm, usually self-sustaining, in which a single frequency or an extremely narrow range of frequencies dominates the animal’s entire physiology and behavior. In such a self-sustaining rhythm, phase is conserved for long intervals, if not indefinitely. These characteristics of biological rhythms create a very special and limited class of problems in data analysis, for which the appropriate and useful techniques are often quite different from those designed for time-series data from other sources.
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© 1981 Plenum Press, New York
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Enright, J.T. (1981). Data Analysis. In: Aschoff, J. (eds) Biological Rhythms. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-6552-9_3
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DOI: https://doi.org/10.1007/978-1-4615-6552-9_3
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