An introduction with medical applications to functional data analysis

Helle Sørensen; Jeff Goldsmith; Laura M Sangalli

doi:10.1002/sim.5989

An introduction with medical applications to functional data analysis

Helle Sørensen, Jeff Goldsmith, Laura M Sangalli

Department of Mathematical Sciences

38 Citations (Scopus)

Abstract

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.

Original language	English
Journal	Statistics in Medicine
Volume	32
Issue number	30
Pages (from-to)	5222-5240
Number of pages	19
ISSN	0277-6715
DOIs	https://doi.org/10.1002/sim.5989
Publication status	Published - 30 Dec 2013

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10.1002/sim.5989

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