Results 231 to 240 of about 80,517 (261)
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2016
Covariance matrix estimation allows the adaptation of Gaussian-based mutation operators to local solution space characteristics.
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Covariance matrix estimation allows the adaptation of Gaussian-based mutation operators to local solution space characteristics.
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A new estimator of covariance matrix
Journal of Statistical Planning and Inference, 2012zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ma, Tiefeng, Jia, Lijie, Su, Yingsheng
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Enhanced Covariance Matrix Estimators in Adaptive Beamforming
2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07, 2007In this paper a number of covariance matrix estimators suggested in the literature are compared in terms of their performance in the context of array signal processing. More specifically they are applied in adaptive beamforming which is known to be sensitive to errors in the covariance matrix estimate and where often only a limited amount of data is ...
Richard Abrahamsson +2 more
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A Robust Heteroskedasticity Consistent Covariance Matrix Estimator
Statistics, 1997To deal with heteroskedasticity of unknown form, this paper suggests to robustly estimate the regression coefficients and then to implement an heteroskedasticity consistent covariance matrix estimator. The robust regression reduces the sample bias of the heteroskedasticity consistent covariance matrix estimator, and does not require the specification ...
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On the estimation of a covariance matrix in designing Parzen classifiers
Pattern Recognition, 1996The design of the Parzen classifiers requires careful attention to the window-width as well as kernel covariance matrices. Although a considerable amount of effort has been devoted to the selection of the window-width, the problem of estimating kernel covariance matrices has received little attention in the past.
Yoshihiko Hamamoto +2 more
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Sparse and Low-Rank Covariance Matrix Estimation
Journal of the Operations Research Society of China, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhou, Shenglong +3 more
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Covariance matrix estimation for left-censored data
Computational Statistics & Data Analysis, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Maiju Pesonen +2 more
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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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An Estimator of Normal Covariance Matrix
Calcutta Statistical Association Bulletin, 1980Solliah (1964), by considering the group of lower triangular matrices, suggested an estimator of the normal covariance matrix Σ when the mean vector is known and the loss function is tr [Formula: see text] His estimator besides being minimax is better than the MLB of Σ.
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Covariance Matrix Estimation Via Network Structure
SSRN Electronic Journal, 2016In this article, we employ a regression formulation to estimate the high dimensional covariance matrix for a given network structure. Using prior information contained in the network relationships, we model the covariance as a polynomial function of the symmetric adjacency matrix.
Wei Lan +3 more
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