Results 51 to 60 of about 531,665 (271)
Graph Sampling for Covariance Estimation
, 2017 In this paper the focus is on subsampling as well as reconstructing the second-order statistics of signals residing on nodes of arbitrary undirected graphs.
Chepuri, Sundeep Prabhakar, Leus, Geert
core +1 more source
Bounds for estimation of covariance matrices from heterogeneous samples [PDF]
, 2008 This correspondence derives lower bounds on the mean-square error (MSE) for the estimation of a covariance matrix mbi Mp, using samples mbi Zk,k=1,...,K, whose covariance matrices mbi Mk are randomly distributed around mbi Mp.
Besson, Olivier +2 more
core +2 more sources
Weighted covariance matrix estimation [PDF]
Computational Statistics & Data Analysis, 2019 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guangren Yang, Yiming Liu, Guangming Pan
openaire +3 more sources
Real‐World Performance of CSF Kappa Free Light Chains in the 2024 McDonald Criteria
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Kappa free light chains (KFLCs) in the cerebrospinal fluid (CSF) have a similar performance to CSF‐restricted oligoclonal bands (OCB) for multiple sclerosis (MS) diagnosis. To help with implementation, we set out to resolve several remaining uncertainties: (1) performance in a real‐world cohort and the 2024 McDonald criteria; (2 ...
Maya M. Leibowitz +11 more
wiley +1 more source
Distributed Moving Horizon Fusion Estimation for Nonlinear Constrained Uncertain Systems
Mathematics, 2023 This paper studies the state estimation of a class of distributed nonlinear systems. A new robust distributed moving horizon fusion estimation (DMHFE) method is proposed to deal with the norm-bounded uncertainties and guarantee the estimation performance.
Shoudong Wang, Binqiang Xue
doaj +1 more source
Group Symmetry and non-Gaussian Covariance Estimation
, 2013 We consider robust covariance estimation with group symmetry constraints. Non-Gaussian covariance estimation, e.g., Tyler scatter estimator and Multivariate Generalized Gaussian distribution methods, usually involve non-convex minimization problems ...
Soloveychik, Ilya, Wiesel, Ami
core +1 more source
High‐dimensional covariance matrix estimation [PDF]
WIREs Computational Statistics, 2019 AbstractCovariance matrix estimation plays an important role in statistical analysis in many fields, including (but not limited to) portfolio allocation and risk management in finance, graphical modeling, and clustering for genes discovery in bioinformatics, Kalman filtering and factor analysis in economics. In this paper, we give a selective review of
openaire +3 more sources
Effects of Biological Sex and Age on Cerebrospinal Fluid Markers—A Retrospective Observational Study
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Cerebrospinal fluid (CSF) analysis is a key diagnostic tool for neurological diseases. To date, only a few studies have investigated in larger cohorts the effect of age and biological sex on diagnostic markers extracted from CSF. Methods For this retrospective observational study, 4163 CSF findings (2012–2020) were evaluated.
Isabel‐Sophie Hafer +3 more
wiley +1 more source
IEEE Access, 2021 Minimum redundancy array (MRA) has the maximum aperture with continuous difference co-array among various sparse arrays with same number of physical sensors, but it is hard to calculate the sensor position of MRA and realize array design by using MRA. To
Geng Wang +4 more
doaj +1 more source
Shrinkage Algorithms for MMSE Covariance Estimation
, 2009 We address covariance estimation in the sense of minimum mean-squared error (MMSE) for Gaussian samples. Specifically, we consider shrinkage methods which are suitable for high dimensional problems with a small number of samples (large p small n). First,
Alfred O. Hero +5 more
core +2 more sources