泊松近似中的非一致界及其在信息距离中的应用. II
概率论
2019-08-15 v2
摘要
我们基于香农相对熵与 R\'enyi/Tsallis 相对距离（包括皮尔逊 ）探讨独立伯努利随机变量分布偏离泊松极限的渐近最优界。本部分推广了第一部分所得结果，并去除了对伯努利分布参数的任何约束。
引用
@article{arxiv.1906.09156,
title = {Non-Uniform Bounds in the Poisson Approximation with Applications to Informational Distances. II},
author = {S. G. Bobkov and G. P. Chistyakov and F. Götze},
journal= {arXiv preprint arXiv:1906.09156},
year = {2019}
}
备注
This version uses our methods to treat R\'enyi/Tsallis relative distances as well. Furthermore, it discusses relations and overlaps with additional results for the non-degenerated cases in the literature we had not been aware of