An introduction with medical applications to functional data analysis. (30th September 2013)

• Record Type: Journal Article
• Authors: Sørensen, Helle; Goldsmith, Jeff; Sangalli, Laura M.; Aalen, Odd O.; Borgan, Ørnulf; Kvaløy, Jan Terje
• Is Part Of: Statistics in medicine. Volume 32:Number 30(2013)
• Page Start: 5222
• Page End: 5240
• Publication Date: 2013-09-30
• Subjects: Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.5989
• Languages: English
• ISSNs: 0277-6715

Abstract

<abstract abstract-type="main" id="sim5989-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <p>Functional data are data that can be represented by suitable functions, such as curves (potentially multi‐dimensional) or surfaces. This paper gives an introduction to some basic but important techniques for the analysis of such data, and we apply the techniques to two datasets from biomedicine. One dataset is about white matter structures in the brain in multiple sclerosis patients; the other dataset is about three‐dimensional vascular geometries collected for the study of cerebral aneurysms. The techniques described are smoothing, alignment, principal component analysis, and regression. Copyright © 2013 John Wiley &amp; Sons, Ltd.</p> </abstract>