关于大协方差阵的带估计的理论和实用价值
On the theoretic and practical merits of the banding estimator for large covariance matrices
摘要:
本文考虑Bickel和Levina(2008)提出的用于估计大协方差阵的带估计量。我们证明了对于一类近似带状协方差阵,带状估计在算子范数下达到率最优,改进了Bickel和Levina(2008)的已有结果.此外,我们提出了一个斯坦的无偏风险估计(当然)类型的方法来选择带宽的带状估计。仿真结果表明,Sure-tuned带估计优于竞争估计。
英文摘要:
This paper considers the banding estimator proposed in Bickel and Levina (2008) for estimation of large covariance matrices. We prove that the banding estimator achieves rate-optimality under the operator norm, for a class of approximately banded covariance matrices, improving the existing results in Bickel and Levina (2008). In addition, we propose a Stein's unbiased risk estimate (Sure)-type approach for selecting the bandwidth for the banding estimator. Simulations indicate that the Sure-tuned banding estimator outperforms competing estimators.
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