Results 261 to 270 of about 55,873 (308)

On the estimation of structured covariance matrices

Automatica, 2012
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ZORZI, MATTIA, FERRANTE, AUGUSTO
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Estimation of hyperspectral covariance matrices

2011 IEEE International Geoscience and Remote Sensing Symposium, 2011
Estimation of covariance matrices is a fundamental step in hyperspectral remote sensing where most detection algorithms make use of the covariance matrix in whitening procedures. We present a simple method to improve the estimation of the eigenvalues of a sample covariance matrix. With the improved eigenvalues we construct an improved covariance matrix.
Avishai Ben-David, Charles E. Davidson
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On testing for homogeneity of the covariance matrices

Korean Journal of Computational & Applied Mathematics, 2001
Summary: Testing equality of covariance matrices of \(k\) populations has long been an interesting issue in statistical inference. To overcome the sparseness of data points in a high-dimensional space and deal with the general cases, we suggest several projection pursuit type statistics.
Zhang, Xiaoning, Jing, Ping, Ji, Xiaoming   +2 more
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Visualizing distributions of covariance matrices

Journal of Data Science, Statistics, and Visualisation
Statistical graphics are generally designed for visualizing data, but in this case our primary goal is to understand complex multivariate models that might be used as prior distributions for models with unknown covariance matrices. Visualizing a distribution of covariance matrices is a step beyond visualizing a single covariance matrix or a single ...
Tomoki Tokuda, Ben Goodrich, Iven Van Mechelen, Andrew Gelman, Francis Tuerlinckx   +4 more
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Semi-tied covariance matrices

Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181), 2002
A standard problem in many classification tasks is how to model feature vectors whose elements are highly correlated. If multi-variate Gaussian distributions are used to model the data then they must have full covariance matrices to accurately do so. This requires a large number of parameters per distribution which restricts the number of distributions
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Graphical Comparison of Covariance Matrices

Australian Journal of Statistics, 1981
SummaryProcedures for comparing within‐group covariance matrices are developed, based on separate analyses of the variances and of the correlations. The variances and the correlations are represented as two two‐way tables, with the columns representing groups. Graphical procedures based on comparisons of linear regressions are presented, by considering
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Testing for Autocorrelation and Equality of Covariance Matrices

Biometrics, 1996
Repeated measures are frequently taken in clinical trials and animal studies. The correlation structure of these measures may follow a pattern such as that of a first-order autoregressive process that can be used to provide an improved statistical analysis.
McKeown, Sean P., Johnson, William D.
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Unconstrained parametrizations for variance-covariance matrices

Statistics and Computing, 1996
The estimation of variance-covariance matrices through optimization of an objective function, such as a log-likelihood function, is usually a difficult numerical problem. Since the estimates should be positive semi-definite matrices, we must use constrained optimization, or employ a parametrization that enforces this condition.
José C. Pinheiro, Douglas M. Bates
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A Bootstrap Comparison of Genetic Covariance Matrices

Biometrics, 1997
Summary: An important problem in evolutionary biology is how population bottlenecks affect additive genetic variance \((V_A)\). When only additive effects are present, a decrease in \(V_A\) is predicted, whereas with many forms of nonadditive interactions, an increase is predicted.
Goodnight, Charles J., Schwartz, James M.   +1 more
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Estimation of Space-Varying Covariance Matrices

2018 25th IEEE International Conference on Image Processing (ICIP), 2018
This paper considers the representation of human trajectories in video signals. These trajectories are modeled by switched dynamical models, based on motion fields that drive the pedestrian during consecutive time intervals. This paper addresses the estimation of uncertainty in trajectory generation by using space-varying covariance matrices estimated ...
Catarina Barata, João Miranda Lemos, Jorge S. Marques   +2 more
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