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Spectral Analysis of Twin Time Series Designs

Published online by Cambridge University Press:  01 August 2014

P.C.M. Molenaar  and
D.I. Boomsma
P.C.M. Molenaar*
Affiliation:
Department of Psychology, University of Amsterdam, Netherlands
D.I. Boomsma
Affiliation:
Department of Experimental Psychology, Free University, Amsterdam, Netherlands
*
Department of Psychology, University of Amsterdam, Weesperplein 8, 1018 XA Amsterdam, Netherlands

Abstract

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The genetic analysis of physiological time series has to accommodate the presence of autocorrelation. This can be accomplished by means of orthogonal transformation of the series, thus enabling the use of standard genetic analysis techniques for the sequence of uncorrelated transforms. In view of the oscillatory character which typifies various physiological time series, it is customary to invoke spectral techniques for the analysis of these series. It can be shown that spectral analysis is an orthogonal transformation that asymptotically resembles principal component analysis. Consequently, standard genetic analysis methods for the uncorrelated spectral transforms may be used. This approach will be illustrated with simulated and real (heart rate) data for univariate twin time series. Furthermore, it will be indicated that the proposed analysis can be readily generalized to multivariate time series.

Keywords

Spectral analysisTwin dataHeart rateTime series
Type
Research Article
Information
Acta geneticae medicae et gemellologiae: twin research , Volume 36 , Issue 1 , January 1987 , pp. 51 - 59
Copyright
Copyright © The International Society for Twin Studies 1987

References

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