Sharp threshold detection based on sup-norm error rates in high-dimensional models
<p style="text-align:justify;"> We propose a new estimator, the thresholded scaled Lasso, in high-dimensional threshold regressions. First, we establish an upper bound on the ℓ∞ estimation error of the scaled Lasso estimator of Lee, Seo, and Shin. This is a nontrivial task as the li...
| Главные авторы: | , , , |
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| Формат: | Journal article |
| Язык: | English |
| Опубликовано: |
Taylor and Francis
2017
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