Results 41 to 50 of about 17,400 (155)
Integrating Data Transformation in Principal Components Analysis [PDF]
, 2015 Principal component analysis (PCA) is a popular dimension-reduction method to reduce the complexity and obtain the informative aspects of high-dimensional datasets.
Hu, Jianhua +2 more
core +3 more sources
Association Between Physical Activity Timing and Metabolic Syndrome in Korea: A Functional Principal Component Approach. [PDF]
Healthcare (Basel)Background: Metabolic syndrome (MetS), characterized by the co-occurrence of obesity, hypertension, hyperglycemia, and dyslipidemia, substantially increases the risk of cardiovascular disease and type 2 diabetes. In South Korea, the prevalence of MetS is
Park S, Jee HJ.
europepmc +2 more sources
Analysing musical performance through functional data analysis: rhythmic structure in Schumann's Träumerei [PDF]
, 2009 Functional data analysis (FDA) is a relatively new branch of statistics devoted to describing and modelling data that are complete functions. Many relevant aspects of musical performance and perception can be understood and quantified as dynamic ...
Almansa, J +1 more
core +2 more sources
Econometrics, 2019 The functional principal components analysis joins the advantages of the principal components analysis and provide analysis of dynamic data. The main difference in both methods is the type of data the PCA is based on multivariate data, whereas the FPCA ...
Mirosława Sztemberg-Lewandowska
semanticscholar +1 more source
Unvealing the Principal Modes of Human Upper Limb Movements through Functional Analysis
Frontiers in Robotics and AI, 2017 The rich variety of human upper limb movements requires an extraordinary coordination of different joints according to specific spatio-temporal patterns. However, unvealing these motor schemes is a challenging task.
Giuseppe Averta +8 more
doaj +1 more source
Recognition and Characterization of Forest Plant Communities through Remote-Sensing NDVI Time Series
Diversity, 2020 Phytosociology is a reference method to classify vegetation that relies on field data. Its classification in hierarchical vegetation units, from plant associations to class level, hierarchically reflects the floristic similarity between different sites ...
Simone Pesaresi +2 more
doaj +1 more source
Statistics in Medicine, 2022 Time‐varying biomarkers reflect important information on disease progression over time. Dynamic prediction for event occurrence on a real‐time basis, utilizing time‐varying information, is crucial in making accurate clinical decisions.
Haolun Shi, Shu Jiang, Jiguo Cao
semanticscholar +1 more source
GECONTEC: Revista Internacional de Gestión del Conocimiento y la Tecnología, 2015 Spanis abstract. El análisis de datos funcionales ha cobrado gran relevancia en los últimos años, convirtiéndose en un importante campo de investigación en la Estadística.
Cristina O. Chávez Chong +2 more
doaj +4 more sources
Functional Factorial K-means Analysis [PDF]
, 2014 A new procedure for simultaneously finding the optimal cluster structure of multivariate functional objects and finding the subspace to represent the cluster structure is presented.
Terada, Yoshikazu, Yamamoto, Michio
core +2 more sources
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
core +3 more sources