Results 31 to 40 of about 7,646,271 (290)
Nonparametric Regression Based on Discretely Sampled Curves
Revstat Statistical Journal, 2020 In the context of nonparametric regression, we study conditions under which the consistency (and rates of convergence) of estimators built from discretely sampled curves can be derived from the consistency of estimators based on the unobserved whole ...
Liliana Forzani +2 more
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Fast Covariance Estimation for High-dimensional Functional Data [PDF]
, 2013 For smoothing covariance functions, we propose two fast algorithms that scale linearly with the number of observations per function. Most available methods and software cannot smooth covariance matrices of dimension $J \times J$ with $J>500$; the ...
Crainiceanu, Ciprian +3 more
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Statistical inferences for functional data
, 2007 With modern technology development, functional data are being observed frequently in many scientific fields. A popular method for analyzing such functional data is ``smoothing first, then estimation.'' That is, statistical inference such as estimation ...
Chen, Jianwei, Zhang, Jin-Ting
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Functional Data Analysis with Increasing Number of Projections [PDF]
, 2013 Functional principal components (FPC's) provide the most important and most extensively used tool for dimension reduction and inference for functional data.
Fremdt, Stefan +3 more
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Functional data clustering: a survey [PDF]
Advances in Data Analysis and Classification, 2013 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jacques, Julien, Preda, Cristian
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Functional Analysis of Variance: An Application to Stock Exchange
Cumhuriyet Science JournalThe concept of "functional data" allows for the representation of data collected repeatedly over a period of time as a continuous function within a specific range on the time axis, rather than as discrete measurement points.
Selin Öğütcü, Nuri Çelik
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Promet (Zagreb), 2022 In traffic monitoring data analysis, the magnitude of traffic density plays an important role in determining the level of traffic congestion. This study proposes a data imputation method for spatio-functional principal component analysis (s-FPCA) and ...
Bing Tang, Yao Hu, Huan Chen
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Functional Autoregression for Sparsely Sampled Data
, 2016 We develop a hierarchical Gaussian process model for forecasting and inference of functional time series data. Unlike existing methods, our approach is especially suited for sparsely or irregularly sampled curves and for curves sampled with non ...
Kowal, Daniel R. +2 more
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Functional principal component analysis of spatially correlated data [PDF]
, 2016 This paper focuses on the analysis of spatially correlated functional data. We propose a parametric model for spatial correlation and the between-curve correlation is modeled by correlating functional principal component scores of the functional data ...
Hooker, Giles, Liu, Chong, Ray, Surajit
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Functional data analysis view of functional near infrared spectroscopy data
Journal of Biomedical Optics, 2013 Functional near infrared spectroscopy (fNIRS) is a powerful tool for the study of oxygenation and hemodynamics of living tissues. Despite the continuous nature of the processes generating the data, analysis of fNIRS data has been limited to discrete-time methods.
Zeinab, Barati +2 more
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