Results 11 to 20 of about 17,400 (155)

Dimensionality reduction of COSMO-RS molecular descriptor using functional principal component analysis (FPCA) for organic solvent mapping. [PDF]

RSC Adv
Methodology for the generation of the σ-potential FPCA mapping.
Ramirez Cardenas LE, Ouaret R, Gerbaud V, Rodriguez Donis I, Thiebaud-Roux S.   +4 more
europepmc   +5 more sources

Lower-limb surface electromyographic differences in roundhouse kicks between elite and sub-elite taekwondo athletes: a functional principal component analysis [PDF]

Frontiers in Physiology
PurposeThis 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, Yifei Wang, Jingyuan Sun, Delong Dong, Shazlin Shaharudin   +4 more
doaj   +3 more sources

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, Ana M. Aguilera, Manuel Escabias   +2 more
doaj   +4 more sources

Predicting progressive vision loss in glaucoma patients using functional principal component analysis and electronic health records [PDF]

Frontiers in Ophthalmology
BackgroundGlaucoma 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, Maxim Sivolella, Cody Carroll, Cody Carroll, Sophia Y. Wang   +4 more
doaj   +3 more sources

Functional principal component analysis (FPCA) on remote sensing data and longitudinal studies

, 2021
This dissertation consists of three main pieces of my Ph.D. dissertation, which shapes my research on multivariate functional data, change-point detection, asynchronous longitudinal data, and remote sensing data applications. The first project is motivated by NASA's first dedicated \ce{CO2} monitoring satellite, the Orbiting Carbon Observatory-2 (OCO-2)
Xinyue Chang
openaire   +5 more sources

Using functional principal component analysis (FPCA) to quantify sitting patterns derived from wearable sensors [PDF]

International Journal of Behavioral Nutrition and Physical Activity
Abstract Background 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, Sheri J. Hartman, Chongzhi Di, Jingjing Zou, Jordan A. Carlson, Paul R. Hibbing, Dori E. Rosenberg, Mikael Anne Greenwood-Hickman, Lindsay Dillon, Andrea Z. LaCroix, Loki Natarajan   +10 more
openaire   +6 more sources

Properties of Design-Based Functional Principal Components Analysis [PDF]

, 2009
This work aims at performing Functional Principal Components Analysis (FPCA) with Horvitz-Thompson estimators when the observations are curves collected with survey sampling techniques.
Benko, Berger, Besse, Besse, Breidt, Camelia Goga, Campbell, Cardot, Cardot, Castro, Catherine Labruère, Chatelin, Chen, Chiou, Croux, Cuevas, Dauxois, Davison, Deville, Deville, Ferraty, Hampel, Hastie, Hervé Cardot, Isaki, James, Kato, Kirkpatrick, Kneip, Mohamed Chaouch, Ramsay, Ramsay, Rice, Robinson, Serfling, Skinner, Särndal, von Mises   +37 more
core   +5 more sources

Functional principal components analysis via penalized rank one approximation [PDF]

, 2008
Two existing approaches to functional principal components analysis (FPCA) are due to Rice and Silverman (1991) and Silverman (1996), both based on maximizing variance but introducing penalization in different ways.
Buja, Andreas, Huang, Jianhua Z., Shen, Haipeng   +2 more
core   +7 more sources

Exploiting upper-limb functional principal components for human-like motion generation of anthropomorphic robots

Journal of NeuroEngineering and Rehabilitation, 2020
Background Human-likeliness of robot movements is a key component to enable a safe and effective human-robot interaction, since it contributes to increase acceptance and motion predictability of robots that have to closely interact with people, e.g.
Giuseppe Averta, Cosimo Della Santina, Gaetano Valenza, Antonio Bicchi, Matteo Bianchi   +4 more
doaj   +2 more sources

Functional Principal Components Analysis of Shanghai Stock Exchange 50 Index

Discrete Dynamics in Nature and Society, 2014
The main purpose of this paper is to explore the principle components of Shanghai stock exchange 50 index by means of functional principal component analysis (FPCA).
Zhiliang Wang, Yalin Sun, Peng Li
doaj   +2 more sources