An introduction with medical applications to functional data analysis
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An introduction with medical applications to functional data analysis. / Sørensen, Helle; Goldsmith, Jeff; Sangalli, Laura M.
I: Statistics in Medicine, Bind 32, Nr. 30, 2013, s. 5222-5240.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - An introduction with medical applications to functional data analysis
AU - Sørensen, Helle
AU - Goldsmith, Jeff
AU - Sangalli, Laura M
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
U2 - 10.1002/sim.5989
DO - 10.1002/sim.5989
M3 - Journal article
C2 - 24114808
VL - 32
SP - 5222
EP - 5240
JO - Statistics in Medicine
JF - Statistics in Medicine
SN - 0277-6715
IS - 30
ER -
ID: 87416948