High-Dimensional Principal Projections
نویسندگان
چکیده
منابع مشابه
High-Dimensional Principal Projections
The Principal Component Analysis (PCA) is a famous technique from multivariate statistics. It is frequently carried out in dimension reduction either for functional data or in a high dimensional framework. To that aim PCA yields the eigenvectors (φ̂i)i of the covariance operator of a sample of interest. Dimension reduction is obtained by projecting on the eigenspaces spanned by the φ̂i’s usually ...
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ژورنال
عنوان ژورنال: Complex Analysis and Operator Theory
سال: 2014
ISSN: 1661-8254,1661-8262
DOI: 10.1007/s11785-014-0371-5