Results 41 to 50 of about 365,137 (249)
BMC Medical Research Methodology, 2016 Background Wastewater-based epidemiology (WBE) is a novel approach in drug use epidemiology which aims to monitor the extent of use of various drugs in a community.
Stefania Salvatore +2 more
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Functional principal component analysis of fMRI data [PDF]
Human Brain Mapping, 2004 AbstractWe describe a principal component analysis (PCA) method for functional magnetic resonance imaging (fMRI) data based on functional data analysis, an advanced nonparametric approach. The data delivered by the fMRI scans are viewed as continuous functions of time sampled at the interscan interval and subject to observational noise, and are used ...
Roberto, Viviani +2 more
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Forecasting Canadian Age-Specific Mortality Rates: Application of Functional Time Series Analysis
Mathematics, 2023 In the insurance and pension industries, as well as in designing social security systems, forecasted mortality rates are of major interest. The current research provides statistical methods based on functional time series analysis to improve mortality ...
Azizur Rahman, Depeng Jiang
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Local Functional Principal Component Analysis [PDF]
Complex Analysis and Operator Theory, 2007 Covariance operators of random functions are crucial tools to study the way random elements concentrate over their support. The principal component analysis of a random function X is well-known from a theoretical viewpoint and extensively used in practical situations. In this work we focus on local covariance operators.
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Computational considerations in functional principal component analysis [PDF]
Computational Statistics, 2007 A general technique of functional principal component analysis (FPCA) is considered from the Hilbert space geometry point of view. Special attention is paid to the equivalence of PCA with different norms and PCA with preliminary transformed data.
Francisco A. Ocaña +2 more
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Contrastive Functional Principal Component Analysis
Proceedings of the AAAI Conference on Artificial IntelligenceAs functional data assumes a central role in contemporary data analysis, the search for meaningful dimension reduction becomes critical due to its inherent infinite-dimensional structure. Traditional methods, such as Functional Principal Component Analysis (FPCA), adeptly explore the overarching structures within the functional data.
Eric Zhang, Didong Li
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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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Functional principal component analysis of spatially correlated data [PDF]
Statistics and Computing, 2016 This paper focuses on the analysis of spatially correlated functional data. The between-curve correlation is modeled by correlating functional principal component scores of the functional data. We propose a Spatial Principal Analysis by Conditional Expectation framework to explicitly estimate spatial correlations and reconstruct individual curves. This
Chong Liu, Surajit Ray, Giles Hooker
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An Advanced Hybrid Logistic Regression Model for Static and Dynamic Mixed Data Classification
IEEE Access, 2022 We consider the binary classification problem of static and dynamic mixed data in this paper. Different from mixed categorical and numerical data, the dynamic variables in the new type of data vary with time and are recorded at discrete time points. This
Mingxue Quan
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Functional connectivity in tactile object discrimination: a principal component analysis of an event related fMRI-Study. [PDF]
PLoS ONE, 2008 BACKGROUND: Tactile object discrimination is an essential human skill that relies on functional connectivity between the neural substrates of motor, somatosensory and supramodal areas.
Susanne Hartmann +6 more
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