Results 11 to 20 of about 3,390,517 (303)
Covariance matrix estimation with heterogeneous samples [PDF]
IEEE Transactions on Signal Processing, 2008 We consider the problem of estimating the covariance matrix Mp of an observation vector, using heterogeneous training samples, i.e., samples whose covariance matrices are not exactly Mp.
Bidon, Stéphanie +2 more
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High‐dimensional covariance matrix estimation [PDF]
WIREs Computational Statistics, 2020 Covariance 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 ...
Lam, Clifford, Clifford Lam
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Sample space-time covariance matrix estimation [PDF]
ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019 Estimation errors are incurred when calculating the sample space-time covariance matrix. We formulate the variance of this estimator when operating on a finite sample set, compare it to known results, and demonstrate its precision in simulations.
Weiss, Stephan +4 more
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The Effects of Data Imputation on Covariance and Inverse Covariance Matrix Estimation
IEEE AccessVarious data analysis techniques and procedures (correlation heatmap, linear discriminant analysis, quadratic discriminant analysis) rely on the estimation of the covariance matrix or its inverse (the precision matrix).
Tuan L. Vo +5 more
doaj +2 more sources
Sparse estimation of a covariance matrix [PDF]
Biometrika, 2011 We suggest a method for estimating a covariance matrix on the basis of a sample of vectors drawn from a multivariate normal distribution. In particular, we penalize the likelihood with a lasso penalty on the entries of the covariance matrix. This penalty plays two important roles: it reduces the effective number of parameters, which is important even ...
Jacob Bien, Robert J. Tibshirani
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Estimation of a covariance matrix with zeros [PDF]
Biometrika, 2007 25 ...
Chaudhuri, S. +2 more
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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
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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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Sparse Covariance Matrix Estimation With Eigenvalue Constraints. [PDF]
J Comput Graph Stat, 2014 We propose a new approach for estimating high-dimensional, positive-definite covariance matrices. Our method extends the generalized thresholding operator by adding an explicit eigenvalue constraint. The estimated covariance matrix simultaneously achieves sparsity and positive definiteness.
Liu H, Wang L, Zhao T.
europepmc +4 more sources
Robust covariance estimation for data fusion from multiple sensors [PDF]
, 2011 This paper addresses the robust estimation of a covariance matrix to express uncertainty when fusing information from multiple sensors. This is a problem of interest in multiple domains and applications, namely, in robotics.
Lazarus, Samuel B. +5 more
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