Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors
We derive a Gaussian approximation result for the maximum of a sum of high-dimensional random vectors. Specifically, we establish conditions under which the distribution of the maximum is approximated by that of the maximum of a sum of the Gaussian random vectors with the same covariance matrices as...
Main Authors: | Chetverikov, Denis (Author), Kato, Kengo (Author), Chernozhukov, Victor V. (Contributor) |
---|---|
Other Authors: | Massachusetts Institute of Technology. Department of Economics (Contributor) |
Format: | Article |
Language: | English |
Published: |
Institute of Mathematical Statistics,
2014-03-17T19:58:22Z.
|
Subjects: | |
Online Access: | Get fulltext |
Similar Items
-
Comparison and anti-concentration bounds for maxima of Gaussian random vectors
by: Chernozhukov, Victor V., et al.
Published: (2016) -
Empirical and multiplier bootstraps for suprema of empirical processes of increasing complexity, and related Gaussian couplings
by: Chetverikov, Denis, et al.
Published: (2018) -
Gaussian approximation of suprema of empirical processes
by: Chetverikov, Denis, et al.
Published: (2018) -
Anti-concentration and honest, adaptive confidence bands
by: Chetverikov, Denis, et al.
Published: (2015) -
Inference on Causal and Structural Parameters using Many Moment Inequalities
by: Chernozhukov, Victor V, et al.
Published: (2019)