Results 51 to 60 of about 1,029,479 (280)
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
doaj +1 more source
Axioms, 2022 This paper shows a visual analysis and the dependence relationships of COVID-19 mortality data in 50 states plus Washington, D.C., from January 2020 to 1 September 2022.
Jong-Min Kim
doaj +1 more source
Sparse multivariate functional principal component analysis
Stat, 2022 We introduce a sparse multivariate functional principal component analysis method by incorporating ideas from the group sparse maximum variance method to multivariate functional data. Our method can avoid the “curse of dimensionality” from a high‐dimensional dataset and enjoy interpretability at the same time. In particular, our unsupervised method can
Jun Song, Kyongwon Kim
openaire +2 more sources
Multiple Change-Point Detection in a Functional Sample via the 𝒢-Sum Process
Mathematics, 2022 We first define the G-CUSUM process and investigate its theoretical aspects including asymptotic behavior. By choosing different sets G, we propose some tests for multiple change-point detections in a functional sample.
Tadas Danielius, Alfredas Račkauskas
doaj +1 more source
Clinical Insights Into Hypercalcemia of Malignancy in Childhood
Pediatric Blood &Cancer, EarlyView.ABSTRACT Hypercalcemia of malignancy (HCM) is a rare but life‐threatening metabolic emergency in children that occurs in less than 1% of pediatric cancer cases, with a reported incidence ranging from 0.4% to 1.0% across different studies. While it is observed in 10%–20% of adult malignancies, pediatric HCM remains relatively uncommon.
Hüseyin Anıl Korkmaz
wiley +1 more source
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 +2 more
doaj +1 more source
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
Pediatric Blood &Cancer, EarlyView.ABSTRACT Arteriovenous malformations (AVMs) are rare, high‐flow, vascular anomalies that can occur either sporadically or as part of a genetic syndrome. AVMs can progress with serious morbidity and even mortality if left unchecked. Sirolimus is an mTOR inhibitor that is effective in low‐flow vascular malformations; however, its role in AVMs is unclear.
Will Swansson +3 more
wiley +1 more source
Functional principal component analysis for cointegrated functional time series
Journal of Time Series Analysis, 2023 Functional principal component analysis (FPCA) has played an important role in the development of functional time series analysis. This note investigates how FPCA can be used to analyze cointegrated functional time series and proposes a modification of FPCA as a novel statistical tool.
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Survivors of childhood acute lymphoblastic leukemia (ALL) often exhibit early deficits in muscle and movement competence, which can compromise long‐term health. Integrative neuromuscular training (INT), a multifaceted approach combining fundamental movement activities with strength exercises, may help address these deficits during ...
Anna Maria Markarian +7 more
wiley +1 more source