Advertisement

TEST

, Volume 26, Issue 4, pp 720–728 | Cite as

Comments on: High-dimensional simultaneous inference with the bootstrap

  • Jelena Bradic
  • Yinchu Zhu
Discussion

Abstract

The authors should be congratulated on their insightful article proposing forms of residual and paired bootstrap methodologies in the context of simultaneous testing in sparse and high-dimensional linear models. We appreciate the clear exposition of their work, and the effectiveness of the proposed method. The authors advocate for the bootstrap of a complete high-dimensional estimate rather than the linearized part of the test statistic. We appreciate the opportunity to comment on several aspects of this article.

Keywords

p-values Robustness Sampling 

Mathematics Subject Classification

62J05 62F03 62F40 

References

  1. Horowitz JL (2001) The bootstrap. In: Heckman JJ, Leamer EE (eds) Handbook of econometrics, chap. 52, vol 5, 1st edn. Elsevier, Amsterdam, pp 3159–3228Google Scholar
  2. Mammen E (1993) Bootstrap and wild bootstrap for high dimensional linear models. Ann Stat 21(1):255–285MathSciNetCrossRefMATHGoogle Scholar
  3. Zhang X, Cheng G (2017) Simultaneous inference for high-dimensional linear models. J Am Stat Assoc 112(518):757–768Google Scholar
  4. Zhu Y, Bradic J (2016) Hypothesis testing in non-sparse high-dimensional linear models. arXiv:1610.02122

Copyright information

© Sociedad de Estadística e Investigación Operativa 2017

Authors and Affiliations

  1. 1.Department of MathematicsUniversity of California, San DiegoLa JollaUSA
  2. 2.Lundquist College of BusinessUniversity of Oregon EugeneEugeneUSA

Personalised recommendations