Central limit theorems for high dimensional dependent data-Reference-Cited by-同舟云学术

Central limit theorems for high dimensional dependent data

Published:2024-02-01 Issue:1 Volume:30 Page:
ISSN:1350-7265
Container-title:Bernoulli
language:
Short-container-title:Bernoulli

Author:

Chang Jinyuan¹,Chen Xiaohui²,Wu Mingcong¹

Affiliation:

1. Joint Laboratory of Data Science and Business Intelligence, Southwestern University of Finance and Economics, Chengdu, China

2. Department of Mathematics, University of Southern California, Los Angeles, CA, USA

Publisher

Bernoulli Society for Mathematical Statistics and Probability

Subject

Statistics and Probability

Reference68 articles.

1. Bentkus, V. (2003). On the dependence of the Berry-Esseen bound on dimension. J. Statist. Plann. Inference 113 385–402. 10.1016/S0378-3758(02)00094-0

2. Raič, M. (2019). A multivariate Berry-Esseen theorem with explicit constants. Bernoulli 25 2824–2853. 10.3150/18-BEJ1072

3. van der Vaart, A.W. (1998). Asymptotic Statistics. Cambridge Series in Statistical and Probabilistic Mathematics 3. Cambridge: Cambridge Univ. Press. 10.1017/CBO9780511802256

4. Wainwright, M.J. (2019). High-Dimensional Statistics: A Non-asymptotic Viewpoint. Cambridge Series in Statistical and Probabilistic Mathematics 48. Cambridge: Cambridge Univ. Press. 10.1017/9781108627771

5. Hörmann, S. (2009). Berry-Esseen bounds for econometric time series. ALEA Lat. Am. J. Probab. Math. Stat. 6 377–397.

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Edge differentially private estimation in the β-model via jittering and method of moments;The Annals of Statistics;2024-04-01

2. A Blockwise Bootstrap-Based Two-Sample Test for High-Dimensional Time Series;Entropy;2024-03-01

3. Central limit theorems for high dimensional dependent data;Bernoulli;2024-02-01

4. Confidence set for group membership;Quantitative Economics;2024

5. Quantitative bounds in the central limit theorem for m-dependent random variables;Latin American Journal of Probability and Mathematical Statistics;2024