Results 21 to 30 of about 365,137 (249)
Characterization of histone modification patterns and prediction of novel promoters using functional principal component analysis. [PDF]
PLoS ONE, 2020 Characterization of distinct histone methylation and acetylation binding patterns in promoters and prediction of novel regulatory regions remains an important area of genomic research, as it is hypothesized that distinct chromatin signatures may specify ...
Mijeong Kim, Shili Lin
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Lower-limb surface electromyographic differences in roundhouse kicks between elite and sub-elite taekwondo athletes: a functional principal component analysis [PDF]
Frontiers in PhysiologyPurposeThis study aimed to investigate the functional characteristics and distinctions in lower-limb electromyography (EMG) time-series data during roundhouse kicks performed by elite (n = 10) and sub-elite (n = 10) Taekwondo athletes, using Functional ...
Jianbo Sun +4 more
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Predicting progressive vision loss in glaucoma patients using functional principal component analysis and electronic health records [PDF]
Frontiers in OphthalmologyBackgroundGlaucoma is a leading cause of irreversible blindness worldwide. Predicting a patient’s future clinical trajectory would help physicians personalize management. We present a novel approach for predicting patient visual field (VF) progression by
Rithvik Krishna Donnipadu +4 more
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Longitudinal functional principal component analysis [PDF]
Electronic Journal of Statistics, 2010 We introduce models for the analysis of functional data observed at multiple time points. The dynamic behavior of functional data is decomposed into a time-dependent population average, baseline (or static) subject-specific variability, longitudinal (or dynamic) subject-specific variability, subject-visit-specific variability and measurement error. The
Greven, Sonja +3 more
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Sparse and Functional Principal Components Analysis [PDF]
2019 IEEE Data Science Workshop (DSW), 2019 The published version of this paper incorrectly thanks "Luofeng Luo" instead of "Luofeng Liao" in the ...
Genevera I. Allen, Michael Weylandt
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On Properties of Functional Principal Components Analysis [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2005 SummaryFunctional data analysis is intrinsically infinite dimensional; functional principal component analysis reduces dimension to a finite level, and points to the most significant components of the data. However, although this technique is often discussed, its properties are not as well understood as they might be.
Hall, Peter, Hosseini-Nasab, Seyed
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Atmosphere, 2023 Functional data are generally curves indexed over a time domain, and land-use regression (LUR) is a promising spatial technique for generating high-resolution spatial estimation of retrospective long-term air pollutants.
Mahmood Taghavi +6 more
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Mathematics, 2023 This paper aims to identify the main determinants of the countries that present contagion during the period 2000–2021, based on the determination of the behavior patterns of 18 stock market indices of 15 of the main economies.
Jorge Omar Razo-De-Anda +2 more
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Computation, 2021 Feature extraction plays an important role in machine learning for signal processing, particularly for low-dimensional data visualization and predictive analytics.
Shengkun Xie
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IEEE Access, 2020 In order to guarantee and improve the product quality, the data-driven fault detection technique has been widely used in industry. For three-way datasets of batch process in industry process (i.e., batch × variable × time), a novel method ...
Fei He, Zhiyan Zhang
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