Cram\'{e}r-type large deviations for samples from a finite population
Zhishui Hu, John Robinson, Qiying Wang

TL;DR
This paper establishes Cramér-type large deviation results for sample means from finite populations and extends these results to the finite population Student t-statistic, under weak conditions.
Contribution
It introduces Cramér-type large deviation principles for finite population means and Student t-statistics, expanding the theoretical understanding of their tail behaviors.
Findings
Large deviation results are comparable to self-normalized deviations for independent variables.
Results are established under weak conditions.
Extensions to the finite population Student t-statistic are provided.
Abstract
Cram\'{e}r-type large deviations for means of samples from a finite population are established under weak conditions. The results are comparable to results for the so-called self-normalized large deviation for independent random variables. Cram\'{e}r-type large deviations for the finite population Student -statistic are also investigated.
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.
