Cosinor-based rhythmometry

Research output: Contribution to journalReview article

138 Citations (Scopus)

Abstract

A brief overview is provided of cosinor-based techniques for the analysis of time series in chronobiology. Conceived as a regression problem, the method is applicable to non-equidistant data, a major advantage. Another dividend is the feasibility of deriving confidence intervals for parameters of rhythmic components of known periods, readily drawn from the least squares procedure, stressing the importance of prior (external) information. Originally developed for the analysis of short and sparse data series, the extended cosinor has been further developed for the analysis of long time series, focusing both on rhythm detection and parameter estimation. Attention is given to the assumptions underlying the use of the cosinor and ways to determine whether they are satisfied. In particular, ways of dealing with non-stationary data are presented. Examples illustrate the use of the different cosinor-based methods, extending their application from the study of circadian rhythms to the mapping of broad time structures (chronomes).

Original languageEnglish (US)
Article number16
JournalTheoretical Biology and Medical Modelling
Volume11
Issue number1
DOIs
StatePublished - Apr 11 2014

Fingerprint

Time series
Parameter estimation
Circadian Rhythm
Sparse Data
Dividend
Least-Squares Analysis
Confidence interval
Least Squares
Parameter Estimation
Regression
Confidence Intervals
Series

Keywords

  • Chronobiology
  • Chronome
  • Circadian
  • Cosinor
  • External information
  • Regression
  • Rhythm parameters
  • Stationarity

Cite this

Cosinor-based rhythmometry. / Cornelissen-Guillaume, Germaine G.

In: Theoretical Biology and Medical Modelling, Vol. 11, No. 1, 16, 11.04.2014.

Research output: Contribution to journalReview article

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