Berry-Esseen Bounds for typical weighted sums
Sergey Bobkov, Gennadiy Chistyakov, Friedrich G\"otze
TL;DR
This paper establishes bounds on how close the distribution of weighted sums of dependent variables is to a normal distribution, under certain correlation conditions, with bounds decreasing at a rate of 1 over the square root of the sample size.
Contribution
It provides new Berry-Esseen bounds for dependent weighted sums under correlation conditions, extending classical results to dependent cases.
Findings
Bounds of order 1/√n for dependent sums
Applicable under correlation-type conditions
Improves understanding of normal approximation for dependent variables
Abstract
Under correlation-type conditions, we derive upper bounds of order for the Kolmogorov distance between the distributions of weighted sums of dependent summands and the normal law.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.