Jiang, Ci-Ren, Aston, John A. D. and Wang, Jane-Ling (2009) Smoothing dynamic positron emission tomography time courses using functional principal components. Working Paper. University of Warwick. Centre for Research in Statistical Methodology, Coventry.

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Abstract

A functional smoothing approach to the analysis of PET time course data is presented. By borrowing information across space and accounting for this pooling through the use of a nonparametric covariate adjustment, it is possible to smooth the PET time course data thus reducing the noise. A new model for functional data analysis, the Multiplicative Nonparametric Random Effects Model, is introduced to more accurately account for the variation in the data. A locally adaptive bandwidth choice helps to determine the correct amount of smoothing at each time point. This preprocessing step to smooth the data then allows Subsequent analysis by methods Such as Spectral Analysis to be substantially improved in terms of their mean squared error.

Item Type:	Working or Discussion Paper (Working Paper)
Subjects:	Q Science > QA Mathematics R Medicine > RC Internal medicine
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Tomography, Emission -- Data processing, Smoothing (Numerical analysis)
Series Name:	Working papers
Journal or Publication Title:	NEUROIMAGE
Publisher:	University of Warwick. Centre for Research in Statistical Methodology
Place of Publication:	Coventry
ISSN:	1053-8119
Date:	1 August 2009
Volume:	Vol.2009
Number:	No.11
Number of Pages:	31
Page Range:	pp. 184-193
Status:	Not Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access
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URI:	http://wrap.warwick.ac.uk/id/eprint/27782

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