arXiv · 2309.04214
Chevet-type inequalities for subexponential Weibull variables and estimates for norms of random matrices
Abstract
We prove two-sided Chevet-type inequalities for independent symmetric Weibull random variables with shape parameter $r\in[1,2]$. We apply them to provide two-sided estimates for operator norms from $\ell_p^n$ to $\ell_q^m$ of random matrices $(a_ib_jX_{i,j})_{i\le m, j\le n}$, in the case when $X_{i,j}$'s are iid symmetric Weibull variables with shape parameter $r\in[1,2]$ or when $X$ is an isotropic log-concave unconditional random matrix. We also show how these Chevet-type inequalities imply two-sided bounds for maximal norms from $\ell_p^n$ to $\ell_q^m$ of submatrices of $X$ in both Weibull and log-concave settings.
Explore related subjects
Keep this discovery
Rafał Latała, Marta Strzelecka. 2023-09-08. Chevet-type inequalities for subexponential Weibull variables and estimates for norms of random matrices. https://doi.org/10.1214/24-ejp1151
Cite the original work for its findings. Save a collection to share your selection of sources.