Bandwidth Selection for High-Dimensional Covariance Matrix Estimation

Yumou Qiu and Song Chen

Journal of the American Statistical Association, 2015, vol. 110, issue 511, 1160-1174

Abstract: The banding estimator of Bickel and Levina and its tapering version of Cai, Zhang, and Zhou are important high-dimensional covariance estimators. Both estimators require a bandwidth parameter. We propose a bandwidth selector for the banding estimator by minimizing an empirical estimate of the expected squared Frobenius norms of the estimation error matrix. The ratio consistency of the bandwidth selector is established. We provide a lower bound for the coverage probability of the underlying bandwidth being contained in an interval around the bandwidth estimate. Extensions to the bandwidth selection for the tapering estimator and threshold level selection for the thresholding covariance estimator are made. Numerical simulations and a case study on sonar spectrum data are conducted to demonstrate the proposed approaches. Supplementary materials for this article are available online.

Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/01621459.2014.950375 (text/html)
Access to full text is restricted to subscribers.

Related works:
Working Paper: Band Width Selection for High Dimensional Covariance Matrix Estimation (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlasa:v:110:y:2015:i:511:p:1160-1174

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/UASA20

DOI: 10.1080/01621459.2014.950375

Access Statistics for this article

Journal of the American Statistical Association is currently edited by Xuming He, Jun Liu, Joseph Ibrahim and Alyson Wilson

More articles in Journal of the American Statistical Association from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().