• DOI:10.1214/14-AOS1221
Corpus ID: 9663766

On asymptotically optimal confidence regions and tests for high-dimensional models

@article{Geer2014OnAO,
  title={On asymptotically optimal confidence regions and tests for high-dimensional models},
  author={S. Geer and Peter Buhlmann and Y. Ritov and Ruben Dezeure},
  journal={Annals of Statistics},
  year={2014},
  volume={42},
  pages={1166-1202}
}

S. Geer, Peter Buhlmann, +1 author Ruben Dezeure

Published 2014

Mathematics

Annals of Statistics

We propose a general method for constructing confidence intervals and statistical tests for single or low-dimensional components of a large parameter vector in a high-dimensional model. It can be easily adjusted for multiplicity taking dependence among tests into account. For linear models, our method is essentially the same as in Zhang and Zhang [J. R. Stat. Soc. Ser. B Stat. Methodol. 76 (2014) 217-242]: we analyze its asymptotic properties and establish its asymptotic optimality in terms of… CONTINUE READING

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