论文标题
假设测试问题的新上限与信息约束
New Upper Bounds in the Hypothesis Testing Problem with Information Constraints
论文作者
论文摘要
我们考虑一个假设检验问题，无法观察到一部分数据。我们的助手观察了错过的数据，可以向我们发送有关它们的有限信息。哪种有限的信息将使我们能够进行最佳的统计推断？特别是，最低信息足以获得相同的结果，就像我们直接观察所有数据一样？我们得出了此最低信息和其他一些类似结果的估计。
We consider a hypothesis testing problem where a part of data cannot be observed. Our helper observes the missed data and can send us a limited amount of information about them. What kind of this limited information will allow us to make the best statistical inference? In particular, what is the minimum information sufficient to obtain the same results as if we directly observed all the data? We derive estimates for this minimum information and some other similar results.
