Broadband angle of arrival estimation methods in a polynomial matrix decomposition framework [PDF]
, 2013 A large family of broadband angle of arrival estimation algorithms are based on the coherent signal subspace (CSS) method, whereby focussing matrices appropriately align covariance matrices across narrowband frequency bins.
Alrmah, Mohamed +4 more
core +1 more source
Asymptotic analysis of the role of spatial sampling for covariance parameter estimation of Gaussian processes [PDF]
, 2013 Covariance parameter estimation of Gaussian processes is analyzed in an asymptotic framework. The spatial sampling is a randomly perturbed regular grid and its deviation from the perfect regular grid is controlled by a single scalar regularity parameter.
Bachoc, François
core +3 more sources
Transposable regularized covariance models with an application to missing data imputation [PDF]
, 2010 Missing data estimation is an important challenge with high-dimensional data arranged in the form of a matrix. Typically this data matrix is transposable, meaning that either the rows, columns or both can be treated as features.
Allen, Genevera I., Tibshirani, Robert
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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
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
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SHrinkage Covariance Estimation Incorporating Prior Biological Knowledge with Applications to High-Dimensional Data [PDF]
, 2011 In ``-omic data'' analysis, information on the structure of covariates are broadly available either from public databases describing gene regulation processes and functional groups such as the Kyoto encyclopedia of genes and genomes (KEGG), or from ...
Boulesteix, Anne-Laure +3 more
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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
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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
SGA based symbol detection and EM channel estimation for MIMO systems [PDF]
, 2006 This paper investigates iterative channel estimation and symbol detection for spatial multiplexing multiple input multiple output (MIMO) systems with frequency flat block fading channels using the expectation-maximization (EM) algorithm.
Andrieu, Christophe +3 more
core +2 more sources