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Robust estimators under a functional common principal components model
(Elsevier Science, 2017-09)
When dealing with several populations of functional data, equality of the covariance operators is often assumed even when seeking for a lower-dimensional approximation to the data. Usually, if this assumption does not hold, ...
Detecting influential observations in principal components and common principal components
(Elsevier Science, 2010-12)
Detecting outlying observations is an important step in any analysis, even when robust estimates are used. In particular, the robustified Mahalanobis distance is a natural measure of outlyingness if one focuses on ellipsoidal ...
Principal Component Analysis For Reservoir Uncertainty Reduction
(Springer HeidelbergHeidelberg, 2016)
PRINCIPAL COMPONENT ANALYSIS OF THE C-13 NMR SHIFTS OF NORBORNYL DERIVATIVES .2. TETRACYCLIC DODECANE DERIVATIVES
(John Wiley & Sons LtdW SussexInglaterra, 1993)
Principal Component Analysis For Reservoir Uncertainty Reduction
(SPRINGER HEIDELBERGHEIDELBERG, 2016)
High-intensity curvilinear movements’ relevance in semi-professional soccer: An approach from principal components analysis
(2021-01-01)
Due to the high number of variables reported from tracking systems, the interest in data reduction techniques has grown. To date, principal component analysis (PCA) has been performed in soccer, but since the results depend ...
Effect of Frozen Storage Time on the Proteolysis of Soft Cheeses Studied by Principal Component Analysis of Proteolytic Profiles
(Wiley Blackwell Publishing, Inc, 2002-12)
Port Salut Argentino cheeses were frozen, stored in a freezer at −22 °C for different periods, and slowly thawed. After thawing, some cheeses were immediately sampled while others were sampled after different refrigerated ...
A characterization of elliptical distributions and some optimality properties of principal components for functional data
(Elsevier Inc, 2014-10)
As in the multivariate setting, the class of elliptical distributions on separable Hilbert spaces serves as an important vehicle and reference point for the development and evaluation of robust methods in functional data ...