Results 11 to 20 of about 1,002,594 (295)
Properties of design-based functional principal components analysis [PDF]
Journal of Statistical Planning and Inference, 2010 Revised version for J. of Statistical Planning and Inference (January 2009)
Cardot, Hervé +3 more
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Multilevel functional principal component analysis
The Annals of Applied Statistics, 2009 Published in at http://dx.doi.org/10.1214/08-AOAS206 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Di, Chong-Zhi +3 more
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Adaptive functional principal components analysis
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2023 Abstract Functional data analysis almost always involves smoothing discrete observations into curves, because they are never observed in continuous time and rarely without error. Although smoothing parameters affect the subsequent inference, data-driven methods for selecting these parameters are not well-developed, frustrated by the ...
Wang, Sunny +2 more
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COVID-19 Data Imputation by Multiple Function-on-Function Principal Component Regression
Mathematics, 2021 The aim of this paper is the imputation of missing data of COVID-19 hospitalized and intensive care curves in several Spanish regions. Taking into account that the curves of cases, deceases and recovered people are completely observed, a function-on ...
Christian Acal +3 more
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Localized Functional Principal Component Analysis [PDF]
Journal of the American Statistical Association, 2015 We propose localized functional principal component analysis (LFPCA), looking for orthogonal basis functions with localized support regions that explain most of the variability of a random process. The LFPCA is formulated as a convex optimization problem through a novel deflated Fantope localization method and is implemented through an efficient ...
Chen, Kehui, Lei, Jing
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New Modeling Approaches Based on Varimax Rotation of Functional Principal Components
Mathematics, 2020 Functional Principal Component Analysis (FPCA) is an important dimension reduction technique to interpret the main modes of functional data variation in terms of a small set of uncorrelated variables.
Christian Acal +2 more
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Sensors, 2021 In this paper, we group South American countries based on the number of infected cases and deaths due to COVID-19. The countries considered are: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Peru, Paraguay, Uruguay, and Venezuela.
Carlos Martin-Barreiro +4 more
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Multi-dimensional functional principal component analysis [PDF]
Statistics and Computing, 2016 Functional principal component analysis is one of the most commonly employed approaches in functional and longitudinal data analysis and we extend it to analyze functional/longitudinal data observed on a general $d$-dimensional domain. The computational issues emerging in the extension are fully addressed with our proposed solutions.
Chen, Lu-Hung, Jiang, Ci-Ren
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Interpretable Functional Principal Component Analysis
Biometrics, 2015 SummaryFunctional principal component analysis (FPCA) is a popular approach to explore major sources of variation in a sample of random curves. These major sources of variation are represented by functional principal components (FPCs). The intervals where the values of FPCs are significant are interpreted as where sample curves have major variations ...
Lin, Zhenhua +2 more
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Parametric Functional Principal Component Analysis
Biometrics, 2017 Summary Functional principal component analysis (FPCA) is a popular approach in functional data analysis to explore major sources of variation in a sample of random curves. These major sources of variation are represented by functional principal components (FPCs).
Sang, Peijun +2 more
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