Results 41 to 50 of about 924,331 (302)
Analytical Nonlinear Shrinkage of Large-Dimensional Covariance Matrices
Annals of Statistics, 2017 This paper introduces a nonlinear shrinkage estimator of the covariance matrix that does not require recovering the population eigenvalues first.
Olivier Ledoit, Michael Wolf
semanticscholar +1 more source
Large Dynamic Covariance Matrices [PDF]
SSRN Electronic Journal, 2016 Second moments of asset returns are important for risk management and portfolio selection. The problem of estimating second moments can be approached from two angles: time series and the cross-section. In time series, the key is to account for conditional heteroskedasticity; a favored model is Dynamic Conditional Correlation (DCC), derived from the ...
Robert F. Engle, Michael Wolf
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Homogeneity Test of Multi-Sample Covariance Matrices in High Dimensions
Mathematics, 2022 In this paper, a new test statistic based on the weighted Frobenius norm of covariance matrices is proposed to test the homogeneity of multi-group population covariance matrices.
Peng Sun, Yincai Tang, Mingxiang Cao
doaj +1 more source
Visualizing Tests for Equality of Covariance Matrices [PDF]
American Statistician, 2018 This article explores a variety of topics related to the question of testing the equality of covariance matrices in multivariate linear models, particularly in the MANOVA setting.
M. Friendly, Matthew J Sigal
semanticscholar +1 more source
M-Matrices as covariance matrices of multinormal distributions
Linear Algebra and its Applications, 1983 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Karlin, Samuel, Rinott, Yosef
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Construction of non-diagonal background error covariance matrices for global chemical data assimilation [PDF]
Geoscientific Model Development, 2011 Chemical data assimilation attempts to optimally use noisy observations along with imperfect model predictions to produce a better estimate of the chemical state of the atmosphere.
K. Singh +5 more
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Functional CLT for sample covariance matrices [PDF]
, 2010 Using Bernstein polynomial approximations, we prove the central limit theorem for linear spectral statistics of sample covariance matrices, indexed by a set of functions with continuous fourth order derivatives on an open interval including $[(1-\sqrt{y})
Bai, Zhidong, Wang, Xiaoying, Zhou, Wang
core +1 more source
Model-based clustering with sparse covariance matrices [PDF]
Statistics and computing, 2017 Finite Gaussian mixture models are widely used for model-based clustering of continuous data. Nevertheless, since the number of model parameters scales quadratically with the number of variables, these models can be easily over-parameterized.
Michael Fop, T. B. Murphy, Luca Scrucca
semanticscholar +1 more source
Transmit Optimization with Improper Gaussian Signaling for Interference Channels [PDF]
, 2013 This paper studies the achievable rates of Gaussian interference channels with additive white Gaussian noise (AWGN), when improper or circularly asymmetric complex Gaussian signaling is applied.
Guan, Yong Liang +4 more
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Large covariance matrices: accurate models without mocks [PDF]
Monthly notices of the Royal Astronomical Society, 2018 Covariance matrix estimation is a persistent challenge for cosmology. We focus on a class of model covariance matrices that can be generated with high accuracy and precision, using a tiny fraction of the computational resources that would be required ...
R. O’Connell, D. Eisenstein
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