STATISTICAL ESTIMATION AND TESTING VIA THE ORDERED l 1 NORM By Małgorzata

@inproceedings{Bogdan2013STATISTICALEA,
  title={STATISTICAL ESTIMATION AND TESTING VIA THE ORDERED l 1 NORM By Małgorzata},
  author={Bogdan and Ewout van den Berg and Weijie Su and Emmanuel J. Cand{\`e}s},
  year={2013}
}
We introduce a novel method for sparse regression and variable selection, which is inspired by modern ideas in multiple testing. Imagine we have observations from the linear model y = Xβ+ z, then we suggest estimating the regression coefficients by means of a new estimator called the ordered lasso, which is the solution to minimize b 1 2‖y −Xb‖ 2 `2 + λ1|b|(1) + λ2|b|(2) + . . .+ λp|b|(p); here, λ1 ≥ λ2 ≥ . . . ≥ λp and |b|(1) ≥ |b|(2) ≥ . . . ≥ |b|(p) is the order statistic of the magnitudes… CONTINUE READING
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