Results 31 to 40 of about 615,565 (289)
A Robust Statistics Approach to Minimum Variance Portfolio Optimization [PDF]
, 2015 We study the design of portfolios under a minimum risk criterion. The performance of the optimized portfolio relies on the accuracy of the estimated covariance matrix of the portfolio asset returns.
Couillet, Romain +2 more
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BAYESIAN INFERENCE FOR A COVARIANCE MATRIX
Conference on Applied Statistics in Agriculture, 2014 Final version, already published in proceedings, Proceedings of 26th Annual Conference on Applied Statistics in Agriculture.
Alvarez, Ignacio +2 more
openaire +4 more sources
IET Radar, Sonar & Navigation, 2023 Benefit from the transmission diversity smoothing (TDS) effect upon coherent targets decorrelation, the kind of adaptive beamformers can be directly applied for multiple‐input multiple‐output (MIMO) sonar applications.
Kuan Fan, Xionghou Liu, Chao Sun
doaj +1 more source
High-Dimensional Covariance Estimation via Constrained Lq-Type Regularization
Mathematics, 2023 High-dimensional covariance matrix estimation is one of the fundamental and important problems in multivariate analysis and has a wide range of applications in many fields.
Xin Wang +3 more
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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
Wiener Filter Approximations Without Covariance Matrix Inversion
IEEE Open Journal of Signal Processing, 2023 In this article, we address the problem of ill-conditioning of the Wiener filter, the optimal linear minimum mean square error estimator. Computing the Wiener filter involves the inverse of the observation covariance matrix.
Pranav U. Damale +2 more
doaj +1 more source
Whitening Degree Evaluation Method to Test Estimate Accuracy of Speckle Covariance Matrix
Leida xuebao, 2017 In the background of sea clutter, the accuracy of adaptive target detection is heavily influenced by the estimated performance of speckle covariance matrix.
Yu Han +3 more
doaj +1 more source
Bayesian Inference for a Covariance Matrix
The Annals of Statistics, 1992 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Leonard, Tom, Hsu, John S. J.
openaire +2 more sources
Estimating the covariance matrix: a new approach [PDF]
Journal of Multivariate Analysis, 2003 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tatsuya Kubokawa, M. S. Srivastava
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Estimating the power spectrum covariance matrix with fewer mock samples [PDF]
, 2015 The covariance matrices of power-spectrum (P(k)) measurements from galaxy surveys are difficult to compute theoretically. The current best practice is to estimate covariance matrices by computing a sample covariance of a large number of mock catalogues ...
Pearson, David W., Samushia, Lado
core +2 more sources