International Monetary Fund

High-Dimensional Covariance Matrix Estimation: Shrinkage Toward a Diagonal Target

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 ...
JSTOR Daily

Robust M Tests without Consistent Estimation of the Asymptotic Covariance Matrix

We extend the KVB approach of Kiefer, Vogelsang, and Bunzel (2000) to constructing robust M tests without consistent estimation of the asymptotic covariance matrix. We demonstrate that, when model ...
JSTOR Daily

Accurate Critical Constants for the One-Sided Approximate Likelihood Ratio Test of a Normal Mean Vector When the Covariance Matrix Is Estimated

Tang, Gnecco, and Geller (1989, Biometrika 76, 577-583) proposed an approximate likelihood ratio (ALR) test of the null hypothesis that a normal mean vector equals a null vector against the ...

Understanding Covariance: How It Indicates Relationships Between Variables

Explore how covariance reveals relationships between variables, its role in financial planning, and its application in the stock market for better investment strategies.
Nature

Graphical Models and Covariance Matrix Estimation

Graphical models provide a robust framework for representing the conditional independence structure between variables through networks, enabling nuanced insight into complex high-dimensional data.