Results 71 to 80 of about 531,665 (271)
, 2016 We establish large sample approximations for an arbitray number of bilinear forms of the sample variance-covariance matrix of a high-dimensional vector time series using $ \ell_1$-bounded and small $\ell_2$-bounded weighting vectors.
Steland, Ansgar, von Sachs, Rainer
core +1 more source
Arthritis Care &Research, EarlyView.Objective Somatic items used in depression assessments can potentially overlap with symptoms related to physical illness, including systemic sclerosis (SSc). No studies have looked at whether somatic depression items may be influenced by diffuse versus limited SSc disease subtypes, which are associated with varying degrees of symptom presentation.
Sophie Hu +110 more
wiley +1 more source
Robust Covariance Estimators Based on Information Divergences and Riemannian Manifold
Entropy, 2018 This paper proposes a class of covariance estimators based on information divergences in heterogeneous environments. In particular, the problem of covariance estimation is reformulated on the Riemannian manifold of Hermitian positive-definite (HPD ...
Xiaoqiang Hua +3 more
doaj +1 more source
Optimal Estimation and Rank Detection for Sparse Spiked Covariance Matrices [PDF]
, 2015 This paper considers sparse spiked covariance matrix models in the high-dimensional setting and studies the minimax estimation of the covariance matrix and the principal subspace as well as the minimax rank detection.
Cai, Tony, Ma, Zongming, Wu, Yihong
core +3 more sources
Advanced Engineering Materials, EarlyView.Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt +8 more
wiley +1 more source
Predicting Atomic Charges in MOFs by Topological Charge Equilibration
Advanced Functional Materials, EarlyView.An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi +2 more
wiley +1 more source
A Reduced Complexity Tensor Approach for Order Selection and Frequency Estimation
IEEE Access, 2021 This paper presents a reduced complexity tensor approach for order selection and subspace-based frequency estimation. The proposed covariance tensor based order selection algorithm, termed as CT-OS, uses singular values of the covariance tensor formed ...
Runyi Yu, Erhan A. Ince
doaj +1 more source
Accelerated Discovery of High Performance Ni3S4/Ni3Mo HER Catalysts via Bayesian Optimization
Advanced Functional Materials, EarlyView.Integrated workflow accelerates the catalyst discovery of hydrogen evolution reaction via Bayesian optimization. An experiment‐trained surrogate model proposes synthesis conditions, guiding iterative refinement using electrochemical performance metrics.
Namuersaihan Namuersaihan +9 more
wiley +1 more source
DOA Estimation Based on Virtual Array Aperture Expansion Using Covariance Fitting Criterion
Remote SensingProviding higher precision Direction of Arrival (DOA) estimation has become a hot topic in the field of array signal processing for parameter estimation in recent years.
Teng Ma +4 more
doaj +1 more source
Regularization for high-dimensional covariance matrix
Special Matrices, 2016 In many applications, high-dimensional problem may occur often for various reasons, for example, when the number of variables under consideration is much bigger than the sample size, i.e., p >> n.
Cui Xiangzhao +5 more
doaj +1 more source