Reproducible Aggregation of Sample-Split Statistics
arxiv(2023)
摘要
Statistical inference is often simplified by sample-splitting. This
simplification comes at the cost of the introduction of randomness that is not
native to the data. We propose a simple procedure for sequentially aggregating
statistics constructed with multiple splits of the same sample. The user
specifies a bound and a nominal error rate. If the procedure is implemented
twice on the same data, the nominal error rate approximates the chance that the
results differ by more than the bound. We provide a non-asymptotic analysis of
the accuracy of the nominal error rate and illustrate the application of the
procedure to several widely applied statistical methods.
更多查看译文
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要