Qiu, Yumou and Chen, Song Xi
(2014):
*Band Width Selection for High Dimensional Covariance Matrix Estimation.*
Forthcoming in: Journal of the American Statistical Association

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## Abstract

The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance estimators. Both estimators require choosing a band width parameter. We propose a band width selector for the banding covariance estimator by minimizing an empirical estimate of the expected squared Frobenius norms of the estimation error matrix. The ratio consistency of the band width selector to the underlying band width is established. We also provide a lower bound for the coverage probability of the underlying band width being contained in an interval around the band width estimate. Extensions to the band width 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 confirm and demonstrate the proposed band width and threshold estimation approaches.

Item Type: | MPRA Paper |
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Original Title: | Band Width Selection for High Dimensional Covariance Matrix Estimation |

English Title: | Band Width Selection for High Dimensional Covariance Matrix Estimation |

Language: | English |

Keywords: | Bandable covariance; Banding estimator; Large $p$, small $n$; Ratio-consistency; Tapering estimator; Thresholding estimator. |

Subjects: | C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C14 - Semiparametric and Nonparametric Methods: General C - Mathematical and Quantitative Methods > C5 - Econometric Modeling |

Item ID: | 59641 |

Depositing User: | Professor Song Xi Chen |

Date Deposited: | 04 Nov 2014 05:45 |

Last Modified: | 30 Sep 2019 21:28 |

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URI: | https://mpra.ub.uni-muenchen.de/id/eprint/59641 |