Results 61 to 70 of about 300,116 (259)
Functional Principal Components Analysis by Choice of Norm
Journal of Multivariate Analysis, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ocaña, F.A. +2 more
openaire +2 more sources
PLoS ONEThis study analysed sprint kayak pacing profiles in order to categorise and compare an athlete's race profile throughout their career. We used functional principal component analysis of normalised velocity data for 500m and 1000m races to quantify pacing.
Harry Estreich +4 more
doaj +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Childhood aplastic anemia (AA) is a rare disease, and both the disease itself and its treatment cause significant morbidity. We aimed to determine the contemporary incidence of childhood AA in Finland, to compare the clinical characteristics of AA against inherited bone marrow failure syndromes (IBMFS) and refractory cytopenia of ...
Lauri‐Matti Kulmala +8 more
wiley +1 more source
Adaptive Functional Principal Component Analysis
, 2023 We introduce Adaptive Functional Principal Component Analysis, a novel method to capture directions of variation in functional data that exhibit sharp changes in smoothness. We first propose a new adaptive scatterplot smoothing technique that is fast and scalable, and then integrate this technique into a probabilistic FPCA framework to adaptively ...
de la Garza, Angel Garcia +3 more
openaire +2 more sources
The Role of Chemotherapy in Pediatric Myoepithelial Carcinoma: A Systematic Review of the Literature
Pediatric Blood &Cancer, EarlyView.ABSTRACT Myoepithelial carcinoma (MEC) in pediatric patients is a rare and aggressive malignancy characterized by heterogeneous morphology and variable molecular features. The optimal role of chemotherapy remains unclear. We conducted a systematic review according to PRISMA 2020 guidelines to evaluate chemotherapy in pediatric and young‐adult patients ...
Marco Salvi +7 more
wiley +1 more source
Robust Bayesian functional principal component analysis
Statistics and ComputingWe develop a robust Bayesian functional principal component analysis (RB-FPCA) method that utilizes the skew elliptical class of distributions to model functional data, which are observed over a continuous domain. This approach effectively captures the primary sources of variation among curves, even in the presence of outliers, and provides a more ...
Jiarui Zhang +2 more
openaire +3 more sources
Bayesian Quantile Regression for Partial Functional Linear Spatial Autoregressive Model
AxiomsWhen performing Bayesian modeling on functional data, the assumption of normality is often made on the model error and thus the results may be sensitive to outliers and/or heavy tailed data.
Dengke Xu +3 more
doaj +1 more source
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Patients with chronic kidney disease undergoing hemodialysis commonly experience reduced physical function, fatigue, poor sleep quality, and impaired health‐related quality of life. Intradialytic exercise has been proposed as a non‐pharmacological strategy to improve these outcomes.
Klebson da Silva Almeida +6 more
wiley +1 more source
S-Estimators for Functional Principal Component Analysis [PDF]
Journal of the American Statistical Association, 2015 Principal component analysis is a widely used technique that provides an optimal lower-dimensional approximation to multivariate or functional datasets. These approximations can be very useful in identifying potential outliers among high-dimensional or functional observations.
Boente Boente, Graciela Lina +1 more
openaire +2 more sources
Bootstrapping Long-Run Covariance of Stationary Functional Time Series
ForecastingA key summary statistic in a stationary functional time series is the long-run covariance function that measures serial dependence. It can be consistently estimated via a kernel sandwich estimator, which is the core of dynamic functional principal ...
Han Lin Shang
doaj +1 more source