Results 261 to 270 of about 623,991 (302)

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
openaire   +2 more sources

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.
openaire   +2 more sources

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
openaire   +1 more source

Iterated Toeplitz approximation of covariance matrices

ICASSP-88., International Conference on Acoustics, Speech, and Signal Processing, 2003
For a signal consisting of p complex exponentials in white noise, it is well known that the true covariance matrix will have the Hermitian Toeplitz structure and that its minimum eigenvalue will have a dimension of M-p (where M is the dimension of the matrix).
D. M. Wikes, Monson H. Hayes
openaire   +2 more sources

A Metric for Covariance Matrices

2003
The paper presents a metric for positive definite covariance matrices. It is a natural expression involving traces and joint eigenvalues of the matrices. It is shown to be the distance coming from a canonical invariant Riemannian metric on the space Sym + (n, ℝ) of real symmetric positive definite ...
Wolfgang Förstner, Boudewijn Moonen
openaire   +1 more source

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
openaire   +1 more source

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
openaire   +1 more source

Covariance Function Matrices

1995
It is actually difficult to characterize directly a covariance function matrix. This becomes easy in the spectral domain on the basis of Cramer’s generalization of the Bochner theorem, which is presented in this chapter. We consider complex covariance functions.
openaire   +1 more source

Analytic inversion of a class of covariance matrices

IEEE Transactions on Information Theory, 1960
The sample covariance matrix arising out of finite memory linear least squares estimation over a set of equally spaced time points, is inverted by spectral methods (operationally referred to as the z transform). It is shown that the complexity of the problem depends only upon the complexity of the input correlation function. The final solution is shown
openaire   +2 more sources

Ordering of Covariance Matrice

Econometric Theory, 1996
CAPPUCCIO, NUNZIO, LUBIAN, DIEGO
openaire   +3 more sources