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Smooth principal components for investigating changes in covariances over time

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Abstract:

Summary.  The complex interrelated nature of multivariate systems can result in relationships and covariance structures that change over time. Smooth principal components analysis is proposed as a means of investigating whether and how the covariance structure of multiple response variables changes over time, after removing a smooth function for the mean, and this is motivated and illustrated by using data from an aircraft technology study and a lake ecosystem. Inferential procedures are investigated in the cases of independent and dependent errors, with a bootstrapping procedure proposed to detect changes in the direction or variance of components.

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1467-9876.2012.01037.x

Affiliations: University of Glasgow, UK

Publication date: November 1, 2012

bpl/rssc/2012/00000061/00000005/art00002
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