sample covariance matrix estimator
LCMV Beamforming for a Novel Wireless Local Positioning System: Nonstationarity and Cyclostationarity Analysis
... novel covariance matrix estimator, which is the critical step for optimal beamforming imple- mentation, in a wireless local positioning system with a pe- riodic signaling ...standard sample ...
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An Adaptive Beamformer Based on Adaptive Covariance Estimator
... Response-Sample Matrix Inversion (MVDR- SMI) method, we propose a novel Adaptive Covariance Estimator (MVDR-ACE) beamformer for adaptation to multiple interference ...data sample in its ...
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Contributions to high dimensional data analysis : some applications of the regularized covariance matrices : a thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Statistics at Massey University, Albany, New Zealand
... the sample covariance in high-dimensional problems is well-known to be ...the sample covariance in a high-dimensional ...the sample covariance matrix, the ridge regular- ...
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Influence Function and Efficiency of the Minimum Covariance Determinant Scatter Matrix Estimator
... and covariance matrix obtained from a ( p+1) subset of observations, which is iterated towards better approximations using Newton-steps (for S) or the so-called C-steps which are used in the FAST-MCD ...the ...
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The minimum weighted covariance determinant estimator
... the sample mean and sample covariance ...or covariance matrices form a cornerstone in multivariate statistical analysis, robust estimators of shape/scatter can be used to construct robust ...
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A New Heteroskedastic Consistent Covariance Matrix Estimator using Deviance Measure
... seriously biased for small samples. There are some alternatives to the estimator of (White, 1980), available the in literature. These estimators are proposed to control the tendency of underestimation of the ...
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Robust Covariance Estimator for Small-Sample Adjustment in the Generalized Estimating Equations: A Simulation Study
... sandwich estimator is common to estimate the covariance matrix of the estimated regression parameter for generalized estimating equation (GEE) method to analyze longitudinal ...robust ...
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Support estimation of a sample space-time covariance matrix
... a sample space- time covariance matrix can be determined from the ground truth space-time covariance, and the variance of the ...the sample-optimum support from the estimate itself, ...
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Asymptotic Theory for Rotated Multivariate GARCH Models
... ance matrix for the first step, and rotates the observed vector to have the identity matrix for its sample covariance ...the covariance matrix, we need finite sixth-order moments ...
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The identification and application of common principal components
... of sample size on the covariance matrix estimators when the two population covariance matrices are ...crossvalid estimator offers any improvement on the accuracy of the unbiased ...
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Robust estimation of biometric data
... robust estimator ˆ C to apply on biometric data analysis involving facial ...the covariance matrix of a multivariate Gaussian distribution by seperately estimating the matrix ...the ...
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The analysis of very small samples of repeated measurements II: a modified box correction
... estimated covariance structure from the estimation of the regression parameters leads to an improvement in the small sample behaviour of in- ...estimated covariance structure is not used in the ...
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A Well-Conditioned and Sparse Estimation of Covariance and Inverse Covariance Matrices Using a Joint Penalty
... of covariance and inverse covariance matrix estimation, where often the interest is to estimate a sparse matrix, the proposed method is flexible in estimat- ing both a sparse and ...
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GMM Estimation of Income Distributions from Grouped Data
... GMM estimator for the beta-2 distribution, apply it to a sample of 8 countries in two time periods, and illustrate how the estimated distributions can be combined to derive a regional distribution, find ...
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Array Aperture Extension Algorithm for 2-D DOA Estimation with L-Shaped Array
... N matrix, and the computational cost is 24 N 3 + 48 N 3 + 54 N 3 = 126 N 3 flops ...N matrix, and the computational burden is 24(2 N ) 3 + 48(2 N ) 3 + 54(2 N ) 3 = 1008 N 3 ...dimensional matrix, the ...
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"On Finite Sample Distributions of the Empirical Likelihood Estimator and the GMM Estimator"
... large sample sizes the GMM estimator and the MEL estimator have approximately the same distribution, but their exact distributions can be quite different for the sample sizes occurring in ...
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Impact of different estimations of the background-error covariance matrix on climate reconstructions based on data assimilation
... background-error covariance matrix in a climate reconstruc- ...background-error covariance matrix estimation techniques improve the skill of the recon- ...the sample covariance ...
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On stability of generalized phase retrieval and generalized affine phase retrieval
... of Z are independent Gaussian random variables with mean value 0 and variance σ 2 . The generalized phase retrieval problem with noise is to estimate x from measurements Y . In this case, we apply the theory of Fisher ...
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Identifying Small Mean Reverting Portfolios
... of sample estimates of the mean reversion versus cardinality ...of sample) mean reversion in the 200 days time window immediately following our sample and also plot average mean reversion versus ...
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Martingale approximation for common factor representation
... In this paper a martingale approximation is used to derive the limiting distribution of sim- ple positive eigenvalues of the sample covariance matrix for a stationary linear process. The derived ...
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