The COV= option must be specified to compute an approximate covariance matrix for the parameter estimates under asymptotic theory for least-squares, maximum-likelihood, or Bayesian estimation, with or ...
The probability (Q) that the estimated between-group covariance matrix is not positive definite is computed for the balanced single classification multivariate analysis of variance with random effects ...
The Annals of Statistics, Vol. 30, No. 4 (Aug., 2002), pp. 1081-1102 (22 pages) This paper analyzes whether standard covariance matrix tests work when dimensionality is large, and in particular larger ...
Graphical models provide a robust framework for representing the conditional independence structure between variables through networks, enabling nuanced insight into complex high-dimensional data.
Download PDF More Formats on IMF eLibrary Order a Print Copy Create Citation This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle ...
We consider the problem of finding a valid covariance matrix in the foreign exchange market given an initial nonpositively semidefinite (non-PSD) estimate of such a matrix. The common no-arbitrage ...
The estimated covariance matrix of the parameter estimates is computed as the inverse Hessian matrix, and for unconstrained problems it should be positive definite. If the final parameter estimates ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback