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Smooth principal components for investigating changes in covariances over time

Miller, C., and Bowman, A. (2012) Smooth principal components for investigating changes in covariances over time. Journal of the Royal Statistical Society: Series C (Applied Statistics), 61 (5). pp. 693-714. ISSN 0035-9254 (doi:10.1111/j.1467-9876.2012.01037.x)

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Abstract

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.

Item Type:Article
Status:Published
Refereed:Yes
Glasgow Author(s):Miller, Dr Claire and Bowman, Prof Adrian
Authors: Miller, C., and Bowman, A.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Journal of the Royal Statistical Society: Series C (Applied Statistics)
ISSN:0035-9254
ISSN (Online):1467-9876
Published Online:24 April 2012

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