Please use this identifier to cite or link to this item: https://doi.org/10.1093/biomet/asr045
Title: Forward adaptive banding for estimating large covariance matrices
Authors: Leng, C. 
Li, B.
Keywords: Adaptive banding
Bic
Lasso
Modified Cholesky decomposition
Variable selection
Issue Date: Dec-2011
Citation: Leng, C., Li, B. (2011-12). Forward adaptive banding for estimating large covariance matrices. Biometrika 98 (4) : 821-830. ScholarBank@NUS Repository. https://doi.org/10.1093/biomet/asr045
Abstract: 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. © 2011 Biometrika Trust.
Source Title: Biometrika
URI: http://scholarbank.nus.edu.sg/handle/10635/105153
ISSN: 00063444
DOI: 10.1093/biomet/asr045
Appears in Collections:Staff Publications

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