... forecasting results. autocovariance dimension reduction factor model functional principal component analysis term structure yield curve C1 C5 E4 G1 Fundamental Research Funds for the Central Universities 10.13039/501100012226 63232103 660041 To model a yield curve that is a collection of yields...

... variability, complexity, intensity, symmetry and magnitude [ 14 ]. These datasets are often large, nonlinear and highly correlated, posing challenges in selecting feature variables that reflected fall risk during subsequent regression prediction [ 1 ]. In this context, principal component analysis (PCA...

... structure within the aging female population, shedding light on important distinctions and patterns among women undergoing menopause. EM algorithm functional data functional principal component analysis mixture regression splines subgroup analysis US National Institutes of Health 10.13039/100000002...

..., and repeated diurnal salivary cortisol assessment in the SPRING pilot (n=79). Principal component analysis was applied anticipating steady-state and “adaptation” mechanisms underlying the repeated physiological measures. Analytic features evidenced these mechanisms, supporting construct validity. Component...

... that are not in LD in the ancestral populations. Using data from moderately differentiated human populations and highly differentiated giraffe populations we show that traditional LD pruning biases F ST and principal component analysis (PCA), which can be alleviated with the adjusted LD measure...

... into the transformed response variable (tPDI), which was more normally distributed. Three multiple regression models were developed based on subsets of variables processed by variable selection and dimensionality reduction methods: Forward Selection, Principal Component Analysis, and Partial Least Squares. The results...

..., we propose a differentially private algorithm to generate low-dimensional synthetic data efficiently from a high-dimensional dataset with a utility guarantee with respect to the Wasserstein distance. A key step of our algorithm is a private principal component analysis (PCA) procedure with a near...

...-spline functional principal component analysis long-term survival analysis non-linear effect National Natural Science Foundation of China 10.13039/501100001809 11971291 12001371 12201487 Shanghai Sailing Program 20YF1434200 China Postdoctoral Science Foundation 10.13039...

... with reproducible and scalable ancestry, quality control, and genome-wide association studies pipelines. python genotype ancestry principal component analysis (PCA) Uniform Manifold Approximation and Projection (UMAP) Intramural Research Program of the NIH National Institute on Aging 10.13039/100000049...

... methods, commonly principal component analysis (PCA), are often used to aid analysis of the resulting multidimensional datasets; PCA can provide denoising prior to further analysis or grouping of pixels into distinct phases with similar signals. However, it is well known that PCA can introduce artifacts...

... based on functional principal component analysis. In many situations, these methods effectively capture the variability in the data. However, when pointwise distributions exhibit skewness or other higher-order characteristics that vary across the function domain, the applicability of these methods...

..., and pore shape factor for identified targets. Additionally, principal component analysis is used to derive recognition factors for fractures and dissolution pores. Applications show that this factor can identify matrix, fracture, and dissolution pore targets in complex background images. By combining...

.... The FTIR spectra exhibited characteristic peaks, denoting the functional groups of the potential compounds present. ICP/MS analysis identified the presence of 14 elements in the tea samples, revealing significant variations in content across the four varieties. principal component analysis (PCA...

... performance of the model. The response variable (PDI) was transformed (tPDI) using the Box-Cox method to meet a normal distribution assumption. To avoid multicollinearity, Principal Component Analysis (PCA) was used to reduce the dimensionality of the numeric factors before building the multiple linear...

...Blasius N Azuhnwi; Akim Omokanye forage value perennial forages principal component analysis Abstract Perennial forages seeded as straight grasses and legumes or in mixtures make a valuable contribution as feed for the beef cattle industry in Alberta. With new varieties constantly being released...

... average projection operator dimensionality reduction mode-wise principal subspace pursuit principal component analysis NSF 10.13039/100000001 DMS-2015285 DMS-2052955 CAREER-2203741 NIH 10.13039/100000002 R01HL169347 R01HL168940 In modern scientific applications, data are often...

... metabolomics recovery shark Abbreviations: PCA principal component analysis TMAO trimethylamine oxide NSERC Discovery Grants RGPIN 473–2012 and RGPIN-2017-03843 Research Council of the University of Antwerp Environmental hypoxia occurs in coastal and open ocean marine ecosystems and varies both...

... principal component analysis (PCA) and reduced rank regression (RRR), and GI cancer risk and GI cancer–caused mortality. Data Source Articles published up to June 2023 in English were eligible for inclusion. The Medline, SCOPUS, Cochrane Library, CINHAL, PsycINFO, ProQuest, and Web of Sciences databases...

... that outperforms the ISH. Resting-state SEEG data from 81 patients with drug-resistant epilepsy undergoing a pre-surgical evaluation at Vanderbilt University Medical Center were collected. Directed connectivity matrices were computed using the alpha band (8–13 Hz). Principal component analysis (PCA) was performed...

... and laboratory findings between MVI-negative and MVI-positive groups, Mann-Whitney U test was used. Additionally, principal component analysis (PCA) was conducted to determine fundamental components. Mann-Whitney U test was applied to determine whether the principal component (PC) scores varied...