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Common Functional Principal Components [PDF]
The Annals of Statistics, 2009 Functional principal component analysis (FPCA) based on the Karhunen-Lo`eve decomposition has been successfully applied in many applications, mainly for one sample problems.
Alois Kneip +2 more
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Hierarchical Principal Components for Data-Driven Multiresolution fMRI Analyses [PDF]
Brain SciencesUnderstanding the organization of neural processing is a fundamental goal of neuroscience. Recent work suggests that these systems are organized as a multiscale hierarchy, with increasingly specialized subsystems nested inside general processing systems.
Korey P. Wylie +3 more
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randPedPCA: rapid approximation of principal components from large pedigrees [PDF]
Genetics Selection EvolutionBackground Pedigrees continue to be extremely important in agriculture and conservation genetics, with the pedigrees of modern breeding programmes easily comprising millions of records.
Hanbin Lee +3 more
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Supporting vectors vs. principal components
AIMS Mathematics, 2023 Let $ T:X\to Y $ be a bounded linear operator between Banach spaces $ X, Y $. A vector $ x_0\in {\mathsf{S}}_X $ in the unit sphere $ {\mathsf{S}}_X $ of $ X $ is called a supporting vector of $ T $ provided that $ \|T(x_0)\| = \sup\{\|T(x)\|:\|x\| = 1\}
Almudena P. Márquez +3 more
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Principal Components of Neural Convolution Filters
IEEE Access, 2022 Convolutions in neural networks are still essential on various vision tasks. To develop neural convolutions, this study focuses on Structured Receptive Field (SRF), representing a convolution filter as a linear combination of widely acting designed ...
Shota Fukuzaki, Masaaki Ikehara
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Modal Principal Component Analysis [PDF]
Neural Computation, 2020 Principal component analysis (PCA) is a widely used method for data processing, such as for dimension reduction and visualization. Standard PCA is known to be sensitive to outliers, and various robust PCA methods have been proposed. It has been shown that the robustness of many statistical methods can be improved using mode estimation instead of mean ...
Sando, Keishi, Hino, Hideitsu
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Principal components analysis of population admixture. [PDF]
PLoS ONE, 2012 With the availability of high-density genotype information, principal components analysis (PCA) is now routinely used to detect and quantify the genetic structure of populations in both population genetics and genetic epidemiology.
Jianzhong Ma, Christopher I Amos
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Principal Dynamical Components [PDF]
Communications on Pure and Applied Mathematics, 2012 AbstractA procedure is proposed for a dimension reduction in time series. Similarly to principal components, the procedure seeks a low‐dimensional manifold that minimizes information loss. Unlike principal components, however, the procedure involves dynamical considerations through the proposal of a predictive dynamical model in the reduced manifold ...
Domínguez de la Iglesia, Manuel +1 more
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Principal component analysis in the spectral analysis of the dynamic laser speckle patterns [PDF]
Journal of the European Optical Society-Rapid Publications, 2014 Dynamic laser speckle is a phenomenon that interprets an optical patterns formed by illuminating a surface under changes with coherent light. Therefore, the dynamic change of the speckle patterns caused by biological material is known as biospeckle ...
Ribeiro K. M. +4 more
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Dynamic Functional Principal Components for Testing Causality
Signals, 2021 In this paper, we investigate the causality in the sense of Granger for functional time series. The concept of causality for functional time series is defined, and a statistical procedure of testing the hypothesis of non-causality is proposed.
Matthieu Saumard, Bilal Hadjadji
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