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Ann Appl Stat. 2015;9(3):1103-1140. doi: 10.1214/15-AOAS842.

SLOPE-ADAPTIVE VARIABLE SELECTION VIA CONVEX OPTIMIZATION.

The annals of applied statistics

Małgorzata Bogdan, Ewout van den Berg, Chiara Sabatti, Weijie Su, Emmanuel J Candès

Affiliations

  1. Department of Mathematics, Wroc?aw University of Technology, 50-370 Wroc?aw, Poland.
  2. Human Language Technologies, IBM T.J. Watson Research Center, Yorktown Heights, New York 10598, USA.
  3. Department of Health Research and Policy, Division of Biostatistics, Stanford University, HRP Redwood Building, Stanford, California 94305, USA.
  4. Department of Statistics, Stanford University, 90 Serra Mall, Sequoia Hall, Stanford, California 94305, USA.
  5. Department of Statistics, Stanford University, 390 Serra Mall, Sequoia Hall, Stanford, California 94305, USA.

PMID: 26709357 PMCID: PMC4689150 DOI: 10.1214/15-AOAS842

Abstract

We introduce a new estimator for the vector of coefficients

Keywords: Lasso; Sparse regression; false discovery rate; sorted ℓ1 penalized estimation (SLOPE); variable selection

References

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  3. PLoS Genet. 2014 Jan 30;10(1):e1004147 - PubMed
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  5. Ann Appl Stat. 2015;9(3):1103-1140 - PubMed
  6. Biometrics. 2008 Mar;64(1):115-23 - PubMed
  7. Ann Stat. 2014 Apr;42(2):413-468 - PubMed

Publication Types

Grant support