Understanding Our Markov Chain Significance Test: A Reply to Cho and Rubinstein-Salzedo

Statistics and Public Policy

Wesley Pegden¹  Alan Frieze¹  Maria Chikina² 

[1] Carnegie Mellon University;University of Pittsburgh;

关键词: gerrymandering;    markov chain;    redistricting;   

DOI  :  10.1080/2330443X.2019.1615396

来源: DOAJ

【 摘 要 】

The article of Cho and Rubinstein-Salzedo seeks to cast doubt on our previous paper, which described a rigorous statistical test which can be applied to reversible Markov chains. In particular, Cho and Rubinstein-Salzedo seem to suggest that the test we describe might not be a reliable indicator of gerrymandering, when the test is applied to certain redistricting Markov chains. However, the examples constructed by Cho and Rubinstein-Salzedo in fact demonstrate a different point: that our test is not the same as another class of gerrymandering tests, which Cho and Rubinstein-Salzedo prefer. But we agree and emphasized this very distinction in our original paper. In this reply, we reply to the criticisms of Cho and Rubinstein-Salzedo, and discuss, more generally, the advantages of the various tests available in the context of detecting gerrymandering of political districtings.

【 授权许可】

Unknown