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  • 标题:Separating Effect From Significance in Markov Chain Tests
  • 本地全文:下载
  • 作者:Maria Chikina ; Alan Frieze ; Jonathan C. Mattingly
  • 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
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