{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T17:12:45Z","timestamp":1792689165786,"version":"4.5.0"},"reference-count":42,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2022,8,17]],"date-time":"2022-08-17T00:00:00Z","timestamp":1660694400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,15]]},"abstract":"<jats:title>Summary<\/jats:title>\n                  <jats:p>The ingenious approach of Chatterjee (2021) to estimate a measure of dependence first proposed by Dette et al. (2013) based on simple rank statistics has quickly caught attention. This measure of dependence has the appealing property of being between 0 and 1, and being 0 or 1 if and only if the corresponding pair of random variables is independent or one is a measurable function of the other almost surely. However, more recent studies (Cao &amp; Bickel 2020; Shi et al. 2022b) showed that independence tests based on Chatterjee\u2019s rank correlation are unfortunately rate inefficient against various local alternatives and they call for variants. We answer this call by proposing an improvement to Chatterjee\u2019s rank correlation that still consistently estimates the same dependence measure, but provably achieves near-parametric efficiency in testing against Gaussian rotation alternatives. This is possible by incorporating many right nearest neighbours in constructing the correlation coefficients. We thus overcome the \u2018 only one disadvantage\u2019 of Chatterjee\u2019s rank correlation (Chatterjee, 2021, \u00a7 7).<\/jats:p>","DOI":"10.1093\/biomet\/asac048","type":"journal-article","created":{"date-parts":[[2022,8,17]],"date-time":"2022-08-17T16:17:54Z","timestamp":1660753074000},"page":"283-299","source":"Crossref","is-referenced-by-count":41,"title":["On boosting the power of Chatterjee\u2019s rank correlation"],"prefix":"10.1093","volume":"110","author":[{"given":"Z","family":"Lin","sequence":"first","affiliation":[{"name":"University of Washington Department of Statistics, , Box 354322, Seattle, Washington 98195, U.S.A"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"F","family":"Han","sequence":"additional","affiliation":[{"name":"University of Washington Department of Statistics, , Box 354322, Seattle, Washington 98195, U.S.A"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,8,17]]},"reference":[{"key":"2023081701162986100_B1","article-title":"Exact detection thresholds for Chatterjee\u2019s correlation","author":"Auddy,","year":"2021"},{"key":"2023081701162986100_B2","doi-asserted-by":"crossref","first-page":"3070","DOI":"10.1214\/21-AOS2073","article-title":"A simple measure of conditional dependence","volume":"49","author":"Azadkia,","year":"2021","journal-title":"Ann. 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