English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

This paper considers the banding estimator proposed in Bickel and Levina(2008) for estimation of large covariance matrices. We prove that the bandingestimator achieves rate-optimality under the operator norm, for a class ofapproximately banded covariance matrices, improving the existing results inBickel and Levina (2008). In addition, we propose a Stein's unbiased riskestimate (Sure)-type approach for selecting the bandwidth for the bandingestimator. Simulations indicate that the Sure-tuned banding estimatoroutperforms competing estimators.

On the theoretic and practical merits of the banding estimator for large covariance matrices