Journal of Applied Probability, Vol. 27, No. 1 (Mar., 1990), pp. 156-170 (15 pages) Let Xt be a discrete-time multivariate stationary process possessing an infinite autoregressive representation and ...

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 ...

This paper proposes a novel shrinkage estimator for high-dimensional covariance matrices by extending the Oracle Approximating Shrinkage (OAS) of Chen et al. (2009) to target the diagonal elements of ...

This article proposes a data-driven method to identify parsimony in the covariance matrix of longitudinal data and to exploit any such parsimony to produce a statistically efficient estimator of the ...

Within statistics, studying too many variables to find meaningful relationships among them is time consuming and expensive. Reducing dimensions (the number of variables) has been widely researched. A ...