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Universality results for largest eigenvalues of some sample covariance matrix ensembles
Universality results largest eigenvalues sample covariance matrix ensembles
2010/4/29
For sample covariance matrices with iid entries with sub-Gaussian
tails, when both the number of samples and the number of variables
become large and the ratio approaches to one, it is a well-known ...
Bayesian Covariance Matrix Estimation using a Mixture of Decomposable Graphical Models
Covariance selection Reduced conditional sampling Variable selection
2010/4/29
Estimating a covariance matrix efficiently and discovering its structure are important
statistical problems with applications in many fields. This article takes a Bayesian
approach to estimate the c...
High Dimensional Covariance Matrix Estimation Using a Factor Model
Factor model diverging dimensionality covariance matrixestimation consistency asymptotic normality optimal portfolio
2010/4/26
High dimensionality comparable to sample size is common in many statistical
problems. We examine covariance matrix estimation in the asymptotic
framework that the dimensionality p tends to ∞ as the ...