@article {Miller:2012:0035-9254:693,
	author = "Miller, Claire and Bowman, Adrian",
	title = "Smooth principal components for investigating changes in covariances over time",
	journal = "Journal of the Royal Statistical Society: Series C (Applied Statistics)",
	volume = "61",
	number = "5",
	year = "2012",
	abstract = "<B>Summary.&#8194;</B> 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.",
	pages = "693-714",
	url = "http://www.ingentaconnect.com/content/bpl/rssc/2012/00000061/00000005/art00002",
	doi = "doi:10.1111/j.1467-9876.2012.01037.x"
}