Results 71 to 80 of about 192,768 (193)
Rational maximum likelihood estimators of Kronecker covariance matrices
Algebraic StatisticsAs is the case for many curved exponential families, the computation of maximum likelihood estimates in a multivariate normal model with a Kronecker covariance structure is typically carried out with an iterative algorithm, specifically, a block-coordinate ascent algorithm.
Drton, Mathias +2 more
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Shrinkage estimation of large covariance matrices: Keep it simple, statistician? [PDF]
Journal of Multivariate Analysis, 2019 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ledoit, Olivier, Wolf, Michael
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Robust Covariance Estimators Based on Information Divergences and Riemannian Manifold
Entropy, 2018 This paper proposes a class of covariance estimators based on information divergences in heterogeneous environments. In particular, the problem of covariance estimation is reformulated on the Riemannian manifold of Hermitian positive-definite (HPD ...
Xiaoqiang Hua +3 more
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Robust Estimates of Covariance Matrices in the Large Dimensional Regime [PDF]
IEEE Transactions on Information Theory, 2014 This article studies the limiting behavior of a class of robust population covariance matrix estimators, originally due to Maronna in 1976, in the regime where both the number of available samples and the population size grow large. Using tools from random matrix theory, we prove that, for sample vectors made of independent entries having some moment ...
Couillet, Romain +2 more
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A Novel Approach to 3D-DOA Estimation of Stationary EM Signals Using Convolutional Neural Networks
Sensors, 2020 This paper proposes a novel three-dimensional direction-of-arrival (3D-DOA) estimation method for electromagnetic (EM) signals using convolutional neural networks (CNN) in a Gaussian or non-Gaussian noise environment.
Dong Chen, Young Hoon Joo
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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
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Best linear unbiased estimation for varying probability with and without replacement sampling
Special Matrices, 2019 When sample survey data with complex design (stratification, clustering, unequal selection or inclusion probabilities, and weighting) are used for linear models, estimation of model parameters and their covariance matrices becomes complicated.
Haslett Stephen
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Frontiers in Applied Mathematics and Statistics, 2019 High-dimensional data from molecular biology possess an intricate correlation structure that is imposed by the molecular interactions between genes and their products forming various different types of gene networks.
Frank Emmert-Streib +6 more
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IEEE AccessA battery management system needs a robust algorithm for online state-of-charge estimation of batteries in different dynamic systems. Due to the ease of implementation, model-based state-of-charge estimation using the extended Kalman filter is popularly ...
Satyaprakash Rout, Satyajit Das
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High-Dimensional Quadratic Discriminant Analysis Under Spiked Covariance Model
IEEE Access, 2020 Quadratic discriminant analysis (QDA) is a widely used classification technique that generalizes the linear discriminant analysis (LDA) classifier to the case of distinct covariance matrices among classes.
Houssem Sifaou +2 more
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