Results 11 to 20 of about 55,908 (306)

Flexible Bayesian Dynamic Modeling of Correlation and Covariance Matrices. [PDF]

Bayesian Anal, 2020
Modeling correlation (and covariance) matrices can be challenging due to the positive-definiteness constraint and potential high-dimensionality. Our approach is to decompose the covariance matrix into the correlation and variance matrices and propose a ...
Lan S, Holbrook A, Elias GA, Fortin NJ, Ombao H, Shahbaba B.   +5 more
europepmc   +3 more sources

Covariance Matrices and the Separability Problem [PDF]

Physical Review Letters, 2007
4 pages, no figures; v3: final version to appear in ...
Gühne, O., Hyllus, P., Gittsovich, O., Eisert, J.   +3 more
openaire   +4 more sources

A Rigorous Feature Extraction Algorithm for Spherical Target Identification in Terrestrial Laser Scanning

Remote Sensing, 2022
Precise and rapid extraction of spherical target features from laser point clouds is critical for achieving high-precision registration of multiple point clouds.
Ronghua Yang, Jing Li, Xiaolin Meng, Yangsheng You   +3 more
doaj   +1 more source

On the Properties of Estimates of Monotonic Mean Vectors for Multivariate Normal Distributions [PDF]

Journal of Statistical Theory and Applications (JSTA), 2015
.Problems concerning estimation of parameters and determination the statistic, when it is known a priori that some of these parameters are subject to certain order restrictions, are of considerable interest.
Abouzar Bazyari
doaj   +1 more source

Millimeter Wave Beamforming Codebook Design via Learning Channel Covariance Matrices Over Riemannian Manifolds

IEEE Access, 2022
Covariance matrices of spatially-correlated wireless channels in millimeter wave (mmWave) vehicular networks can be employed to design environment-aware beamforming codebooks.
Imtiaz Nasim, Ahmed S. Ibrahim
doaj   +1 more source

Local Laws for Sparse Sample Covariance Matrices

Mathematics, 2022
We proved the local Marchenko–Pastur law for sparse sample covariance matrices that corresponded to rectangular observation matrices of order n×m with n/m→y (where y>0) and sparse probability npn>logβn (where β>0).
Alexander N. Tikhomirov, Dmitry A. Timushev   +1 more
doaj   +1 more source

A Novel Adaptive Kalman Filter With Colored Measurement Noise

IEEE Access, 2018
In this paper, a novel variational Bayesian-based adaptive Kalman filter (VBAKF) is proposed to solve the problem of a linear state-space model with colored measurement noise and inaccurate noise covariance matrices.
Yonggang Zhang, Guangle Jia, Ning Li, Mingming Bai   +3 more
doaj   +1 more source

Large Dynamic Covariance Matrices [PDF]

Journal of Business & Economic Statistics, 2017
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 ...
Engle, Robert F, Ledoit, Olivier, Wolf, Michael   +2 more
openaire   +4 more sources

Estimation Method of Covariance Matrix in Atmospheric Inversion of CO2 Emissions [PDF]

E3S Web of Conferences
Atmospheric inversion of CO2 Emissions is based on the correction of prior carbon dioxide flux inventories using concentration monitoring data and atmospheric transport models to obtain posterior carbon dioxide flux.
Han Yubin, Ren Ge, Zhao Shiqi, Du Kailun, Lin Hong   +4 more
doaj   +1 more source

Spiked sample covariance matrices with possibly multiple bulk components [PDF]

, 2020
In this paper, we study the convergent limits and rates of the eigenvalues and eigenvectors for spiked sample covariance matrices whose spectrum can have multiple bulk components.
Ding, Xiucai, Xiucai Ding
core   +1 more source