Results 51 to 60 of about 623,991 (302)
Assesment of covariance processing with GAIA for nuclear data uncertainty propagation [PDF]
EPJ Web of ConferencesNuclear data uncertainties are provided as covariance matrices in standard nuclear data libraries and propagating them trough neutronics simulations helps quantify the associated uncertainties on the final result. However, processing these matrices often
Sole Pierre +3 more
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Choroid plexus volume (CPV) has been proposed as a neuro‐immunological marker of multiple sclerosis (MS), but its relevance in myelin oligodendrocyte glycoprotein antibody–associated disease (MOGAD) remains uncertain. We analyzed CPV in 43 individuals with MOGAD, 48 with MS, and 44 healthy controls using a Bayesian Gaussian mixture modeling ...
Jae‐Won Hyun +4 more
wiley +1 more source
SensorsIn this article, an improved real-valued dimension-reduction MUSIC (IRDR-MUSIC) algorithm is proposed for a crossed-dipole array. Initially, conjugate symmetry of the spatial component in the manifold vector is derived such that two real-valued matrices ...
Hao Nan +3 more
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Log‐Euclidean bag of words for human action recognition
IET Computer Vision, 2015 Representing videos by densely extracted local space–time features has recently become a popular approach for analysing actions. In this study, the authors tackle the problem of categorising human actions by devising bag of words (BoWs) models based on ...
Masoud Faraki +2 more
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Forecasting Covariance Matrices: A Mixed Approach [PDF]
Journal of Financial Econometrics, 2014 In this article, we introduce a new method of forecasting large-dimensional covariance matrices by exploiting the theoretical and empirical potential of mixing forecasts derived from different information sets. The main theoretical contribution of the article is to find the conditions under which a mixed approach (MA) provides a smaller mean squared ...
Halbleib, Roxana, Voev, Valeri
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Diffusion Basis Spectrum Imaging of Tissue Microstructure and Early Treatment in Multiple Sclerosis
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Conventional MRI cannot resolve the coexisting pathological processes within multiple sclerosis tissue. Diffusion Basis Spectrum Imaging decomposes the diffusion signal into fiber, cell, and hindered ratios indexing axonal integrity, cellularity, and extracellular space, respectively.
Apisit Kaewsanit +10 more
wiley +1 more source
On the Significance of Covariance for Constraining Theoretical Models from Galaxy Observables
The Astrophysical JournalIn this study, we investigate the impact of covariance within uncertainties on the inference of cosmological and astrophysical parameters, specifically focusing on galaxy stellar mass functions derived from the CAMELS simulation suite.
Yongseok Jo +3 more
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IEEE Access, 2018 This paper addresses the estimation of large-dimensional covariance matrices under both normal and nonnormal distributions. The shrinkage estimators are constructed by convexly combining the sample covariance matrix and a structured target matrix.
Jianbo Li, Jie Zhou, Bin Zhang
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Quadratic shrinkage for large covariance matrices [PDF]
Bernoulli, 2019 This paper constructs a new estimator for large covariance matrices by drawing a bridge between the classic Stein (1975) estimator in finite samples and recent progress under large-dimensional asymptotics. The estimator keeps the eigenvectors of the sample covariance matrix and applies shrinkage to the inverse sample eigenvalues.
Ledoit, Olivier, Wolf, Michael
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Covariance and correlations matrices.
, 2015 Covariance and correlations matrices.
Mats Jirstrand (727382) +5 more
core +1 more source