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. (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: | Articles |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Miller, Professor 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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