Functional principal component model for high-dimensional brain imaging
نویسندگان
چکیده
منابع مشابه
Functional principal component model for high-dimensional brain imaging
We explore a connection between the singular value decomposition (SVD) and functional principal component analysis (FPCA) models in high-dimensional brain imaging applications. We formally link right singular vectors to principal scores of FPCA. This, combined with the fact that left singular vectors estimate principal components, allows us to deploy the numerical efficiency of SVD to fully est...
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ژورنال
عنوان ژورنال: NeuroImage
سال: 2011
ISSN: 1053-8119
DOI: 10.1016/j.neuroimage.2011.05.085