Anders Bredahl Kock, David Preinerstorfer
arXiv 19 Oct 2023 · Mathematics — Statistics Theory · publishedStatistics & Probability Letters (2024) · 2 citations (OpenAlex)
arXiv:2310.12863 · PDF · DOI · OpenAlex · Extracted main text
In this article, we study the critical growth rates of dimension below which Gaussian critical values can be used for hypothesis testing but beyond which they cannot. We are particularly interested in how these growth rates depend on the number of moments that the observations possess.
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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 | Zhang, D. and W. B. Wu (2017) Gaussian approximation for high dimensional time series | 1.000 | 6 | 3 | 100% |
| 2 | Chernozhukov, V., D. Chetverikov, K. Kato, and Y. Koike (2023) a): High-dimensional data bootstrap | 0.928 | 5 | 3 | 80% |
| 3 | Bentkus, V (2003) On the dependence of the Berry–Esseen bound on dimension | 0.511 | 2 | 1 | 100% |
| 4 | Bentkus, V (2005) A Lyapunov-type bound in $R^d$ | 0.405 | 1 | 1 | 100% |
| 5 | Chernozhukov, V., D. Chetverikov, and K. Kato (2013) Gaussian approximations and multiplier bootstrap for maxima of sums of high-dimensional random vectors | 0.405 | 1 | 1 | 100% |
| 6 | Chernozhukov, V., D. Chetverikov, and K. Kato (2017) Central limit theorems and bootstrap in high dimensions | 0.405 | 1 | 1 | 100% |
| 7 | Chernozhukov, V., D. Chetverikov, and Y. Koike (2023) b): Nearly optimal central limit theorem and bootstrap approximations in high dimensions | 0.405 | 1 | 1 | 100% |
| 8 | Chernozhuokov, V., D. Chetverikov, K. Kato, and Y. Koike (2022) Improved central limit theorem and bootstrap approximations in high dimensions | 0.405 | 1 | 1 | 100% |
| 9 | Das, D. and S. Lahiri (2021) Central Limit Theorem in high dimensions: The optimal bound on dimension growth rate | 0.405 | 1 | 1 | 100% |
| 10 | Deng, H. and C.-H. Zhang (2020) Beyond Gaussian approximation: Bootstrap for maxima of sums of independent random vectors | 0.405 | 1 | 1 | 100% |
Showing the top 10 of 24 scored citations.
arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.
| Citing paper | Intensity | Mentions | Sections | |
|---|---|---|---|---|
| 1 | Enhanced power enhancements for testing many moment equalities: Beyond the $2$- and $$-norm | 0.644 | 2 | 2 |
| 2 | Yurinskii's Coupling for Martingales | 0.511 | 2 | 2 |