Uniform post selection inference for LAD regression models

@inproceedings{Belloni2013UniformPS,
  title={Uniform post selection inference for LAD regression models},
  author={Alexandre Belloni and Victor Chernozhukov and Kengo Kato},
  year={2013}
}
We develop uniformly valid confidence regions for a regression coefficient in a high-dimensional sparse LAD (least absolute deviation or median) regression model. The setting is one where the number of regressors p could be large in comparison to the sample size n, but only s « n of them are needed to accurately describe the regression function. Our new methods are based on the instrumental LAD regression estimator that assembles the optimal estimating equation from either post l- penalised LAD… CONTINUE READING

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