文章基本信息

标题：Separating Effect From Significance in Markov Chain Tests
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作者：Maria Chikina ; Alan Frieze ; Jonathan C. Mattingly 等
期刊名称：Statistics and Public Policy
电子版ISSN：2330-443X
出版年度：2020
卷号：7
期号：1
页码：1-15
DOI：10.1080/2330443X.2020.1806763
出版社：Taylor and Francis Ltd
摘要：We give qualitative and quantitative improvements to theorems which enable significance testing in Markov chains, with a particular eye toward the goal of enabling strong, interpretable, and statistically rigorous claims of political gerrymandering. Our results can be used to demonstrate at a desired significance level that a given Markov chain state (e.g., a districting) is extremely unusual (rather than just atypical) with respect to the fragility of its characteristics in the chain. We also provide theorems specialized to leverage quantitative improvements when there is a product structure in the underlying probability space, as can occur due to geographical constraints on districtings.
关键词：Gerrymandering Markov chain Outlier