Literature DB >> 6723267

Analysis of circadian rhythms by fitting a least squares sine curve.

D S Hickey, J L Kirkland, S B Lucas, M Lye.   

Abstract

A method that fits a least squares sine curve to both point and averaged time series data is described. The method includes a full regression analysis and extends the current "cosinor" approach. Developments include estimation of the linear trend and fitting secondary wave forms.

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Year:  1984        PMID： 6723267     DOI： 10.1016/0010-4825(84)90008-8

Source DB:  PubMed          Journal:  Comput Biol Med        ISSN： 0010-4825            Impact factor:   4.589


  3 in total

1.  A Partially Linear Regression Model for Data from an Outcome-Dependent Sampling Design.

Authors:  Haibo Zhou; Jinhong You; Guoyou Qin; Matthew P Longnecker
Journal:  J R Stat Soc Ser C Appl Stat       Date:  2011-08       Impact factor: 1.864

2.  Modeling biological rhythms in failure time data.

Authors:  Naser B Elkum; James D Myles
Journal:  J Circadian Rhythms       Date:  2006-11-07

3.  Free-Living Humans Cross Cardiovascular Disease Risk Categories Due to Daily Rhythms in Cholesterol and Triglycerides.

Authors:  Azure D Grant; Gary I Wolf
Journal:  J Circadian Rhythms       Date:  2019-04-24
  3 in total

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