Sara van de Geer - The Debiased Lasso

From Katie Gentilello September 11th, 2018

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In the third lecture we use sparsity to establish confidence intervals for a parameter of interest. The idea is to use the penalized estimator as an initial estimator in a one-step Newton-Raphson procedure. Functionals of this new estimator that can under certain conditions be shown to be asymptotically normally distributed. We show that in the high-dimensional case, one may further profit from sparsity conditions if the inverse Hessian of the problem is not sparse.

Tags: triad distinguished lecture seriesfall 2018recorded by gtlibrarygeorgia tech

name: Sara van de Geer
biography: Sara van de Geer has been Full Professor at the Seminar for Statistics at ETH Zurich since September 2005. Her main field of research is mathematical statistics, with special interest in high-dimensional problems.
Date: September 6th, 2018
Appears In: Open Scholarship

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Sara van de Geer - The Debiased Lasso

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