Harold D. Chiang, Kengo Kato, Yuya Sasaki
arXiv 10 Sep 2020 · Econometrics · publishedJournal of the American Statistical Association (2021) · 3 citations (OpenAlex)
arXiv:2009.05150 · PDF · DOI · OpenAlex · Extracted main text
We consider inference for high-dimensional separately and jointly exchangeable arrays where the dimensions may be much larger than the sample sizes. For both exchangeable arrays, we first derive high-dimensional central limit theorems over the rectangles and subsequently develop novel multiplier bootstraps with theoretical guarantees. These theoretical results rely on new technical tools such as Hoeffding-type decomposition and maximal inequalities for the degenerate components in the Hoeffiding-type decomposition for the exchangeable arrays. We exhibit applications of our methods to uniform confidence bands for density estimation under joint exchangeability and penalty choice for $\ell_1$-penalized regression under separate exchangeability. Extensive simulations demonstrate precise uniform coverage rates. We illustrate by constructing uniform confidence bands for international trade network densities.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | Graham, B. S., F. Niu, and J. L. Powell (2019) Kernel density estimation for undirected dyadic data | 1.000 | 5 | 3 | 100% |
| 2 | Kallenberg, O (2006) Probabilistic Symmetries and Invariance Principles | 1.000 | 5 | 3 | 100% |
| 3 | Silverman, B. W (1976) Limit theorems for dissociated random variables | 0.874 | 6 | 2 | 100% |
| 4 | Davezies, L., X. D'Haultfoeuille, and Y. Guyonvarch (2020) Empirical process results for exchangeable arrays | 0.776 | 15 | 4 | 47% |
| 5 | Chernozhukov, V., D. Chetverikov, K. Kato, and Y. Koike (2019) Improved central limit theorem and bootstrap approximations in high dimensions | 0.737 | 3 | 3 | 67% |
| 6 | Graham, B. S., F. Niu, and J. L. Powell (2020) Minimax risk and uniform convergence rates for nonparametric dyadic regression | 0.737 | 3 | 2 | 100% |
| 7 | Menzel, K (2017) Bootstrap with clustering in two or more dimensions | 0.737 | 3 | 2 | 100% |
| 8 | Chen, X. and K. Kato (2020) Jackknife multiplier bootstrap: finite sample approximations to the $U$-process supremum with applications | 0.644 | 3 | 2 | 67% |
| 9 | Andrews, D. W (2005) Cross-section regression with common shocks | 0.644 | 2 | 2 | 100% |
| 10 | Head, K. and T. Mayer (2014) Gravity equations: Workhorse, toolkit, and cookbook | 0.644 | 2 | 2 | 100% |
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