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Stock price prediction using principal components. [PDF]
PLoS ONE, 2020 The literature provides strong evidence that stock price values can be predicted from past price data. Principal component analysis (PCA) identifies a small number of principle components that explain most of the variation in a data set.
Mahsa Ghorbani, Edwin K P Chong
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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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On the Correlation between Random Variables and their Principal Components [PDF]
Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki, 2023 The article attempts to find an algebraic formula describing the correlation coefficients between random variables and the principal components representing them.
Zenon Gniazdowski
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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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New Interpretation of Principal Components Analysis [PDF]
Zeszyty Naukowe Warszawskiej Wyższej Szkoły Informatyki, 2017 A new look on the principal component analysis has been presented. Firstly, a geometric interpretation of determination coefficient was shown.
Zenon Gniazdowski
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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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