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 ...

Hiroshi Kurata, Takeaki Kariya, Least Upper Bound for the Covariance Matrix of a Generalized Least Squares Estimator in Regression with Applications to a Seemingly Unrelated Regression Model and a ...

Covariance matrix estimation, crucial for multivariate inference, faces significant challenges when the number of variables rivals or exceeds the sample size.

Graphical Models and Covariance Matrix Estimation Publication Trend The graph below shows the total number of publications each year in Graphical Models and Covariance Matrix Estimation.