Model selection for high-dimensional linear regression with dependent observations

Ching-Kang Ing National Tsing Hua University

Statistics Theory and Methods mathscidoc:2103.33001

Annals of Statistics, 48, 2020.9
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Best m-term approximations, high-dimensional Akaike’s information criterion, orthogonal greedy algorithm, sparsity conditions, time series
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@inproceedings{ching-kang2020model,
  title={MODEL SELECTION FOR HIGH-DIMENSIONAL LINEAR REGRESSION WITH DEPENDENT OBSERVATIONS},
  author={Ching-Kang Ing},
  url={http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20210304232817198141737},
  booktitle={Annals of Statistics},
  volume={48},
  year={2020},
}
Ching-Kang Ing. MODEL SELECTION FOR HIGH-DIMENSIONAL LINEAR REGRESSION WITH DEPENDENT OBSERVATIONS. 2020. Vol. 48. In Annals of Statistics. http://archive.ymsc.tsinghua.edu.cn/pacm_paperurl/20210304232817198141737.
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