- Referenced in 9 articles
- limit spectra of sample covariance matrices. Models from random matrix theory (RMT) are increasingly used ... from a multivariate distribution with a given covariance matrix. Under high-dimensional asymptotics, there ... distribution of eigenvalues of the population covariance matrix (the population spectral distribution ... estimation and hypothesis testing for covariance matrices. Our proposal, implemented in open source software...
- Referenced in 8 articles
- latent behavior states; 3) biased and correlated random walk movement models, including ”activity centers” associated ... forces; 4) user-specified design matrices and constraints for covariate modelling of parameters using formulas...
- Referenced in 6 articles
- sphere. The efficient simulation of isotropic Gaussian random fields on the unit sphere ... necessary conditional covariance matrices is derived and simulations demonstrate the performance of the algorithm...
- Referenced in 4 articles
- covariance parameters. This is accomplished through compactly supported basis functions and a Markov random field ... basis coefficients. These features lead to sparse matrices for the computations and this package makes ... geometries besides a rectangular domain. The Markov random field approach combined with a basis function ... also the flexibility for estimating non-stationary covariances and also the case when the observations...
- Referenced in 2 articles
- imputing missing values, following missing completely at random patterns, exploiting the relationships among variables ... data, to estimate the covariance structure of incomplete data matrices, or to impute the missing...
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- regularized estimators of large covariance matrices. Four regularized methods are implemented: banding, tapering, hard-thresholding ... considered: K-fold CV and random CV. Usually K-fold CV use K-1 folds...
- Referenced in 1 article
- marginal means and covariance matrices of linear mixed models as group-specific plug-in estimators ... profiles and more complex longitudinal models with random effects. Subsequently, we present multivariate extensions ... parsimonious parametrization are proposed: multivariate random effects models and covariance pattern models with a Kronecker...
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- Almost any workflow involves computing results, and that...