University of Cambridge > Talks.cam > Statistics > Two-sample testing of high-dimensional linear regression coefficients via complementary sketching

Two-sample testing of high-dimensional linear regression coefficients via complementary sketching

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Qingyuan Zhao.

This talk has been canceled/deleted

We introduce a new methodology for two-sample testing of high-dimensional linear regression coefficients without assuming that those coefficients are individually estimable. The procedure works by first projecting the matrices of covariates and response vectors along directions that are complementary in sign in a subset of the coordinates, a process which we call ‘complementary sketching’. The resulting projected covariates and responses are aggregated to form two test statistics. We show that our procedure has essentially optimal asymptotic power under Gaussian designs with a general class of design covariance matrices when the difference between the two regression coefficients is sparse and dense respectively. Simulations confirm that our methods perform well in a broad class of settings.

This talk is part of the Statistics series.

Tell a friend about this talk:

This talk is included in these lists:

This talk is not included in any other list

Note that ex-directory lists are not shown.

 

© 2006-2024 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity