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Symmetrization for high dimensional dependent random vari...
Jonathan B. Hill · 2025-05-31 · via math.ST updates on arXiv.org

We establish a generic symmetrization property for dependent random variables $\{x_{t}\}_{t=1}^{n}$ on $\mathbb{R}^{p}$, where $p$ $>>$ $n$ is allowed. We link $\mathbb{E}ψ(\max_{1\leq i\leq p}|1/n\sum_{t=1}^{n}(x_{i,t}$ $-$ $\mathbb{E}x_{i,t})|)$ to $\mathbb{E}ψ(\max_{1\leq i\leq p}|1/n$ $\sum_{t=1}^{n}η_{t}(x_{i,t}$ $-$ $\mathbb{E}% x_{i,t})|)$ for non-decreasing convex $ψ$ $:$ $[0,\infty )$ $\rightarrow $ $\mathbb{R}$, where $\{η_{t}\}_{t=1}^{n}$ are block-wise independent random variables, with a remainder term based on high dimensional Gaussian approximations that need not hold at a high level. Conventional usage of $% η_{t}(x_{i,t}$ $-$ $\tilde{x}_{i,t})$ with $\{\tilde{x}% _{i,t}\}_{t=1}^{n} $ an independent copy of $\{x_{i,t}\}_{t=1}^{n}$, and Rademacher $η_{t}$, is not required in a generic environment, although we may trivially replace $\mathbb{E}x_{i,t}$ with $\tilde{x}_{i,t}$. In the latter case with Rademacher $η_{t}$ our result reduces to classic symmetrization under independence. We bound and therefore verify the Gaussian approximations in mixing and physical dependence settings, thus bounding $\mathbb{E}ψ(\max_{1\leq i\leq p}|1/n\sum_{t=1}^{n}(x_{i,t}$ $-$ $\mathbb{E}x_{i,t})|)$; and apply the main result to a generic % Nemirovski (2000)-like $\mathcal{L}_{q}$-maximal moment bound for $\mathbb{E}\max_{1\leq i\leq p}|1/n\sum_{t=1}^{n}(x_{i,t}$ $-$ $\mathbb{E}x_{i,t})|^{q}$, $q$ $\geq $ $1$.