Localized Functional Principal Component Analysis. [PDF]
J Am Stat Assoc, 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 K, Lei J.
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MFPCA: Multiscale Functional Principal Component Analysis. [PDF]
Proc AAAI Conf Artif Intell, 2019 We consider the problem of performing dimension reduction on heteroscedastic functional data where the variance is in different scales over entire domain. The aim of this paper is to propose a novel multiscale functional principal component analysis (MFPCA) approach to address such heteroscedastic issue.
Lin Z, Zhu H.
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Functional Principal Component Analysis and Randomized Sparse Clustering Algorithm for Medical Image Analysis. [PDF]
PLoS ONE, 2015 Due to the advancement in sensor technology, the growing large medical image data have the ability to visualize the anatomical changes in biological tissues. As a consequence, the medical images have the potential to enhance the diagnosis of disease, the
Nan Lin +3 more
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Using functional principal component analysis (FPCA) to quantify sitting patterns derived from wearable sensors [PDF]
International Journal of Behavioral Nutrition and Physical ActivityBackground Sedentary behavior (SB) is a recognized risk factor for many chronic diseases. ActiGraph and activPAL are two commonly used wearable accelerometers in SB research. The former measures body movement and the latter measures body posture.
Rong W. Zablocki +10 more
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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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Multilevel sparse functional principal component analysis. [PDF]
Stat, 2014 We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis was proposed recently for such data when functions are ...
Di C, Crainiceanu CM, Jank WS.
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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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Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait Mapping [PDF]
G3: Genes, Genomes, Genetics, 2016 We previously proposed a simple regression-based method to map quantitative trait loci underlying function-valued phenotypes. In order to better handle the case of noisy phenotype measurements and accommodate the correlation structure among time points ...
Il-Youp Kwak +3 more
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Principal Component Analysis of Munich Functional Developmental Diagnosis
Pediatric Reports, 2021 Objectives: Munich Functional Developmental Diagnosis (MFDD) is a scale for assessing the psychomotor development of children in the first months or years of life.
Grażyna Pazera +3 more
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