Forward adaptive banding for estimating large covariance matrices

• 成果类型: Article
• 署名作者: Leng, Chenlei; Li, Bo
• 署名单位: National University of Singapore; Tsinghua University
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asr045
• 发表日期: 2011
• 页码: 821830
• 关键词: VARIABLE SELECTION; shrinkage

摘要

We propose a simple forward adaptive banding method for estimating large covariance matrices using the modified Cholesky decomposition. This approach requires the fitting of a prespecified set of models due to the adaptive banding structure and can be efficiently implemented. Aside from its computational attractiveness, we propose a novel Bayes information criterion that gives consistent model selection for estimating high dimensional covariance matrices. The method compares favourably to its competitors in simulation study.