21 citations · 21 across the 4 of their papers we have counts for
6 papers
High-dimensional Data Bootstrap
Victor Chernozhukov, Denis Chetverikov, Kengo Kato +1
This article reviews recent progress in high-dimensional bootstrap. We first review high-dimensional central limit theorems for distributions of sample mean vectors over the rectan…
Weighted-average quantile regression
Denis Chetverikov, Yukun Liu, Aleh Tsyvinski
In this paper, we introduce the weighted-average quantile regression framework, , where is a dependent variable, is a vector of covariates,…
Nearly optimal central limit theorem and bootstrap approximations in high dimensions
Victor Chernozhukov, Denis Chetverikov, Yuta Koike
In this paper, we derive new, nearly optimal bounds for the Gaussian approximation to scaled averages of independent high-dimensional centered random vectors ov…
High-Dimensional Econometrics and Regularized GMM
Alexandre Belloni, Victor Chernozhukov, Denis Chetverikov +2
This chapter presents key concepts and theoretical results for analyzing estimation and inference in high-dimensional models. High-dimensional models are characterized by having a…
Detailed proof of Nazarov's inequality
Victor Chernozhukov, Denis Chetverikov, Kengo Kato
The purpose of this note is to provide a detailed proof of Nazarov's inequality stated in Lemma A.1 in Chernozhukov, Chetverikov, and Kato (2017, Annals of Probability).
Double/Debiased/Neyman Machine Learning of Treatment Effects
Victor Chernozhukov, Denis Chetverikov, Mert Demirer +3
Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, and Newey (2016) provide a generic double/de-biased machine learning (DML) approach for obtaining valid inferential statements ab…