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Structured covariance matrix estimation: a parametric approach
2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100), 2002The problem of estimating a positive semi-definite Toeplitz covariance matrix consisting of a low rank matrix plus a scaled identity from noisy data arises in many applications. We propose a computationally attractive (noniterative) covariance matrix estimator with certain optimality properties.
Magnus Jansson, Björn E. Ottersten
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On the Estimation of Polychoric Correlations and their Asymptotic Covariance Matrix
Psychometrika, 1994A general theory for parametric inference in contingency tables is outlined. Estimation of polychoric correlations is seen as a special case of this theory. The asymptotic covariance matrix of the estimated polychoric correlations is derived for the case when the thresholds are estimated from the univariate marginals and the polychoric correlations are
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DoA Estimation Using Neural Network-Based Covariance Matrix Reconstruction
IEEE Signal Processing Letters, 2021Wolfgang Utschick, Andreas Barthelme
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Augmented Covariance Matrix Reconstruction for DOA Estimation Using Difference Coarray
IEEE Transactions on Signal Processing, 2021Zhi Zheng +2 more
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Covariance Matrix Estimation Under Low-Rank Factor Model With Nonnegative Correlations
IEEE Transactions on Signal Processing, 2022Perez Palomar Daniel +2 more
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The Bias of a Heteroskedasticity Consistent Covariance Matrix Estimator
Econometrica, 1987Chesher, Andrew, Jewitt, Ian
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Covariance matrix estimation and classification with limited training data
IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996D A Landgrebe
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High-dimensional covariance matrix estimation with missing observations
Bernoulli, 2014Karim Lounici
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