• DOI:10.1198/jasa.2009.tm08647
Corpus ID: 1263254

p-Values for High-Dimensional Regression

@article{Meinshausen2008pValuesFH,
  title={p-Values for High-Dimensional Regression},
  author={N. Meinshausen and Lukas Meier and Peter B{\"u}hlmann},
  journal={Journal of the American Statistical Association},
  year={2008},
  volume={104},
  pages={1671 - 1681}
}

N. Meinshausen, Lukas Meier, Peter Bühlmann

Published 2008

Mathematics

Journal of the American Statistical Association

Assigning significance in high-dimensional regression is challenging. Most computationally efficient selection algorithms cannot guard against inclusion of noise variables. Asymptotically valid p-values are not available. An exception is a recent proposal by Wasserman and Roeder that splits the data into two parts. The number of variables is then reduced to a manageable size using the first split, while classical variable selection techniques can be applied to the remaining variables, using the… CONTINUE READING

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