Covariance assisted screening and estimation

Tracy Ke Jiashun Jin Jianqing Fan

Statistics Theory and Methods mathscidoc:1912.43341

Annals of statistics, 42, (6), 2202, 2014.11
Consider a linear model Y= X + z, where X= X n, p and z~ N (0, I n). The vector is unknown and it is of interest to separate its nonzero coordinates from the zero ones (ie, variable selection). Motivated by examples in long-memory time series (Fan and Yao, 2003) and the change-point problem (Bhattacharya, 1994), we are primarily interested in the case where the Gram matrix G= X X is non-sparse but sparsifiable by a finite order linear filter. We focus on the regime where signals are both rare and weak so that successful variable selection is very challenging but is still possible.
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@inproceedings{tracy2014covariance,
  title={Covariance assisted screening and estimation},
  author={Tracy Ke, Jiashun Jin, and Jianqing Fan},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113820058972901},
  booktitle={Annals of statistics},
  volume={42},
  number={6},
  pages={2202},
  year={2014},
}
Tracy Ke, Jiashun Jin, and Jianqing Fan. Covariance assisted screening and estimation. 2014. Vol. 42. In Annals of statistics. pp.2202. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20191221113820058972901.
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