Results 191 to 200 of about 547,601 (228)
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DOA estimation using modified covariance matrix
2012 Loughborough Antennas & Propagation Conference (LAPC), 2012This work proposes a new method to estimate direction-of-arrival (DOA) for directional antenna arrays. An obvious modification in the proposed method is the inclusion of changes of array gain in matrix calculation. This method is proposed in order to suit the characteristic of directional antenna array.
Rahmat Sanudin +2 more
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Consistent Covariance Matrix Estimation for Dependent Heterogeneous Processes
Econometrica, 1992This note presents a simple consistency proof for general kernel-based covariance estimators, requiring the existence of only slightly more than second moments. Covariance stationarity is not required. Instead, the data are assumed to satisfy either an \(\alpha\)-mixing or a \(\phi\)-mixing condition.
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Consistent Covariance Matrix Estimation with Spatially Dependent Panel Data
Review of Economics and Statistics, 1998J. Driscoll, Aart C. Kraay
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Covariance Matrix Estimation in Linear Models
Journal of the American Statistical Association, 1970Abstract In regression analysis with heteroscedastic and/or correlated errors, the usual assumption is that the covariance matrix σ of the errors is completely specified, except perhaps for a scalar multiplier. This condition is relaxed in this paper by assuming only that σ has a certain pattern; for example, that σ is diagonal or partitionable into a ...
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Equivariant estimators of the covariance matrix
Canadian Journal of Statistics, 1990AbstractGiven a Wishart matrix S [S ∽ Wp(n, Σ)] and an independent multinomial vector X [X ∽ Np (μ, Σ)], equivariant estimators of Σ are proposed. These estimators dominate the best multiple of S and the Stein‐type truncated estimators.
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Covariance Matrix Estimation in High Dimensions
2013Statistical structures start with covariance matrices. In practice, we must estimate the covariance matrix from the big data. One may think this chapter should be more basic than Chaps. 7 and 8—thus should be treated earlier chapters. Recent work on compressed sensing and low-rank matrix recovery supports the idea that sparsity can be exploited for ...
Robert Qiu, Michael Wicks
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The biofilm matrix: multitasking in a shared space
Nature Reviews Microbiology, 2022Hans-Curt Flemming +2 more
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Robust Covariance Matrix Estimation using Random Matrix Theory
Proceedings of the 6th Joint International Conference on Data Science & Management of Data (10th ACM IKDD CODS and 28th COMAD), 2023Samruddhi Deshmukh +2 more
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Cell–extracellular matrix mechanotransduction in 3D
Nature Reviews Molecular Cell Biology, 2023Aashrith Saraswathibhatla +2 more
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