estimation error covariance matrix
A Hybrid Adaptive Unscented Kalman Filter Algorithm
... the estimation window for the UKF which the covariance matrix of uncertainly noise is estimated at the present ...posterior estimation and exponential weighting was proposed by authors ...
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Sample space-time covariance matrix estimation
... modelling error that is incurred when estimating a space-time covariance matrix from a finite sample set — this is affected by the size of the set, but also the ground truth space-time ...
5
Support estimation of a sample space-time covariance matrix
... this estimate should be calculated as this direct impacts on the error propagation and computational complexity of any subsequent processing. As a byproduct of the analysis of the variance of R[τ], in [21], an ...
5
An $\ell_{\infty}$ Eigenvector Perturbation Bound and Its Application
... the covariance matrix as a low rank component ...residual covariance of the idiosyncratic components is often modeled by a sparse component ...estimated covariance matrix A e = Σ, which ...
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Impact of a time-dependent background error covariance matrix on air quality analysis
... background error covariance matrix ...a covariance matrix is to estimate it from an ensemble of perturbed assimilation ...resulting covariance matrix is strongly time ...
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Impact of different estimations of the background-error covariance matrix on climate reconstructions based on data assimilation
... provides estimation of the truth, represented by the ensemble mean, and the per- turbations from the mean are used to estimate the uncer- tainty, represented by the background-error covariance ma- ...
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A Bootstrap Method for Error Estimation in Randomized Matrix Multiplication
... With regard to the statistics literature, our work builds upon a line of research dealing with “multiplier bootstrap methods” in high-dimensional problems (Chernozhukov et al., 2013, 2014, 2017). Such methods are ...
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Estimating model error covariance matrix parameters in extended Kalman filtering
... model error tuning problem can be viewed as a pa- rameter estimation problem in state space ...parameter estimation in stochastic dif- ferential equation (SDE) models (Singer, 2002) and time se- ries ...
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CS-SFD Algorithm for GNSS Anti-Jamming Receivers
... space-time covariance matrix is perfectly ...calculation error of the covariance matrix in the case of fewer snapshots, which may lead to remarkable performance ...interference ...
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Band Width Selection for High Dimensional Covariance Matrix Estimation
... The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance esti- mators. Both estimators require a band width parameter. We ...
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Analysis error covariance versus posterior covariance in variational data assimilation
... The error in the optimal solution (or ‘analysis error’) is naturally defined as a difference between the solution u and the true state u t ; this error is quantified by the analysis error ...
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On errors in variables estimation with unknown noise variance ratio
... Identifiability of the model is recovered by construct- ing two estimating equations corresponding to the two clusters. The idea generalizes to problems involv- ing more than two unknown parameters in the mea- surement ...
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Impact of space-time covariance estimation errors on a parahermitian matrix EVD
... of estimation errors in the sample space-time covariance matrix on its parahermitian matrix eigenvalue ...the estimation error in the space-time covariance matrix, ...
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The Direction-of-Arrival and Polarization Estimation Using Coprime Array: a Reconstructed Covariance Matrix Approach
... that there are K = 14 far-field narrowband completely polarized electromagnetic wave sources impinging upon the array. These source signals are uniformly distributed from − 52 ◦ to 52 ◦ , auxiliary polarization 28 ◦ to 80 ...
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Automatic positive semidefinate HAC covariance matrix and GMM estimation
... HAC covariance matrix esti- mators + Rather than weight the estimated autocovariances as in the standard lag kernel method , we initially smooth the data observations on the random vector process itself ...
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Off -Grid Direction-of-Arrival Estimation Using a Sparse Array Covariance Matrix
... DOA estimation using a sparse array covariance matrix, so the method proposed here is referred to as off-grid sparse array covariance matrix ...array covariance matrix into ...
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Petrol and Crude Oil Prices: Asymmetric Price Transmission
... of estimation caused by the autocorrelation present was overcome by the Wald tests based on the Newey-West adjusted variance-covariance matrix with different ...
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A fast STAP method using persymmetry covariance matrix estimation for clutter suppression in airborne MIMO radar
... persymmetry covariance matrix estimation in the airborne MIMO radar is ...clutter covariance matrix is estimated by the original data and the constructed ...
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Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models
... a reduced conditional MCMC sampler for decomposable graphical models, where the co- variance matrix is integrated out of all conditional distributions and is not generated in the MCMC. Our approach does not ...
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Group Lasso Estimation of High-dimensional Covariance Matrices
... the covariance matrix Σ by expanding the process X into a dictionary of basis ...suitable matrix regression model. This new approach to covariance estimation is well adapted to the case ...
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