Results 31 to 40 of about 192,869 (306)
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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Regularized estimation of large covariance matrices
The Annals of Statistics, 2008 This paper considers estimating a covariance matrix of $p$ variables from $n$ observations by either banding or tapering the sample covariance matrix, or estimating a banded version of the inverse of the covariance. We show that these estimates are consistent in the operator norm as long as $(\log p)/n\to0$, and obtain explicit rates.
Bickel, Peter J., Levina, Elizaveta
openaire +4 more sources
Covariance matrices of S robust regression estimators
Journal of Statistical Computation and Simulation, 2021 Asymptotic properties of robust regression estimators are well known. However, it is not always clear what is the best strategy for confidence intervals and hypothesis testing when the sample size is not very large, since the distribution of residuals coming from robust estimates has unknown properties for small samples.
S. Salini +4 more
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Covariance estimation via fiducial inference
Statistical Theory and Related Fields, 2021 As a classical problem, covariance estimation has drawn much attention from the statistical community for decades. Much work has been done under the frequentist and Bayesian frameworks.
W. Jenny Shi +3 more
doaj +1 more source
Kronecker Sum Decompositions of Space-Time Data [PDF]
, 2013 In this paper we consider the use of the space vs. time Kronecker product decomposition in the estimation of covariance matrices for spatio-temporal data.
Greenewald, Kristjan +2 more
core +1 more source
The DOA Estimation Method for Low-Altitude Targets under the Background of Impulse Noise
Sensors, 2022 Due to the discontinuity of ocean waves and mountains, there are often multipath propagation effects and obvious pulse characteristics in low-altitude detection.
Bin Lin +4 more
doaj +1 more source
Optimal Estimation and Rank Detection for Sparse Spiked Covariance Matrices [PDF]
, 2015 This paper considers sparse spiked covariance matrix models in the high-dimensional setting and studies the minimax estimation of the covariance matrix and the principal subspace as well as the minimax rank detection.
Cai, Tony, Ma, Zongming, Wu, Yihong
core +3 more sources
Estimation of Shortest Path Covariance Matrices
, 2020 We study the sample complexity of estimating the covariance matrix $\mathbf \in \mathbb{R}^{d\times d}$ of a distribution $\mathcal D$ over $\mathbb{R}^d$ given independent samples, under the assumption that $\mathbf $ is graph-structured. In particular, we focus on shortest path covariance matrices, where the covariance between any two measurements
Maity, Raj Kumar, Musco, Cameron
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DOA Estimation of Completely Polarized Signals by One-Bit Cross-Dipole Arrays
IEEE AccessThe one-bit cross-dipole array employs one-bit quantization to reduce the sampling system overhead while extracting polarization information from electromagnetic signals, thereby lowering the system complexity of the polarization array.
Yu Wang +5 more
doaj +1 more source
A High-Resolution and Low-Complexity DOA Estimation Method with Unfolded Coprime Linear Arrays
Sensors, 2019 The direction-of-arrivals (DOA) estimation with an unfolded coprime linear array (UCLA) has been investigated because of its large aperture and full degrees of freedom (DOFs).
Wei He, Xiao Yang, Yide Wang
doaj +1 more source