Forward adaptive banding for estimating large covariance matrices

Chenlei Leng and Bo Li

Biometrika, 2011, vol. 98, issue 4, 821-830

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. Copyright 2011, Oxford University Press.

Date: 2011
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