Bayes linear covariance matrix adjustment [PDF]
, 1995 In this thesis, a Bayes linear methodology for the adjustment of covariance matrices is presented and discussed. A geometric framework for quantifying uncertainties about covariance matrices is set up, and an inner-product for spaces of random matrices ...
Wilkinson, Darren James
core
Knowledge-aided Bayesian covariance matrix estimation in compound-Gaussian clutter [PDF]
, 2010 We address the problem of estimating a covariance matrix R using K samples zk whose covariance matrices are kR, where k are random variables. This problem naturally arises in radar applications in the case of compound-Gaussian clutter. In contrast to the
Bandiera, Francesco +6 more
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Performance analysis of beamformers using generalized loading of the covariance matrix in the presence of random steering vector errors [PDF]
, 2005 Robust adaptive beamforming is a key issue in array applications where there exist uncertainties about the steering vector of interest. Diagonal loading is one of the most popular techniques to improve robustness.
Besson, Olivier, Vincent, François
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Large-scale portfolios using realized covariance matrix: evidence from the Japanese stock market [PDF]
This paper examines effects of realized covariance matrix estimators based on high-frequency data on large-scale minimum-variance equity portfolio optimization.
Masato Ubukata
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The affine equivariant sign covariance matrix: asymptotic behavior and efficiencies. [PDF]
We consider the affine equivariant sign covariance matrix (SCM) introduced by Visuri et al. (J. Statist. Plann. Inference 91 (2000) 557). The population SCM is shown to be proportional to the inverse of the regular covariance matrix. The eigenvectors and
Croux, Christophe, Ollila, E, Oja, H
core
Testing of a Structures Covariance Matrix for Three-Level Repeated Measures Data. [PDF]
This paper considers the problem of estimating, and testing for, a Kronecker product covariance structure of three-level (multiple time points (p), multiple sites (u), and multiple response variables (q)) multivariate data.
Ricardo Leiva, Anuradha Roy
core
Evaluating the covariance matrix constraints for data-driven statistical human motion reconstruction
, 2014 This paper presents the evaluation process of the character's motion reconstruction while constraints are applied to the covariance matrix of the motion prior learning process.
Christos Mousas +5 more
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Bootstrapping heteroskedasticity consistent covariance matrix estimator [PDF]
Recent results of Cribari-Neto and Zarkos (1999) show that bootstrap methods can be successfully used to estimate a heteroskedasticity robust covariance matrix estimator. In this paper, we show that the wild bootstrap estimator can be calculated directly,
Emmanuel Flachaire
core
Leida xuebaoThis paper addresses the multi-target direct localization problem for moving single stations using the coprime difference co-array. Existing methods based on matrix norm minimization often suffer from underutilization of redundant data from virtual array
Hongzhen WANG +3 more
doaj +1 more source
Satellite Interference Source Direction of Arrival (DOA) Estimation Based on Frequency Domain Covariance Matrix Reconstruction. [PDF]
Sensors (Basel), 2023 Yao J +5 more
europepmc +1 more source