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

Institut for Matematiske Fag

38 Citationer (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.

Originalsprog	Engelsk
Tidsskrift	Statistics in Medicine
Vol/bind	32
Udgave nummer	30
Sider (fra-til)	5222-5240
Antal sider	19
ISSN	0277-6715
DOI	https://doi.org/10.1002/sim.5989
Status	Udgivet - 30 dec. 2013

Adgang til dokumentet

10.1002/sim.5989

Citationsformater

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