{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T16:41:49Z","timestamp":1792600909637,"version":"4.5.0"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T00:00:00Z","timestamp":1658361600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,2,11]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>We propose a new inference framework called localized conformal prediction. It generalizes the framework of conformal prediction by offering a single-test-sample adaptive construction that emphasizes a local region around this test sample, and can be combined with different conformal scores. The proposed framework enjoys an assumption-free finite sample marginal coverage guarantee, and it also offers additional local coverage guarantees under suitable assumptions. We demonstrate how to change from conformal prediction to localized conformal prediction using several conformal scores, and we illustrate a potential gain via numerical examples.<\/jats:p>","DOI":"10.1093\/biomet\/asac040","type":"journal-article","created":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T12:10:44Z","timestamp":1658405444000},"page":"33-50","source":"Crossref","is-referenced-by-count":73,"title":["Localized conformal prediction: a generalized inference framework for conformal prediction"],"prefix":"10.1093","volume":"110","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0609-1073","authenticated-orcid":false,"given":"Leying","family":"Guan","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Yale University , 60 College Street, New Haven, Connecticut 06520, U.S.A"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2022,7,21]]},"reference":[{"key":"2023021111212402200_B1","article-title":"Conformal prediction under covariate shift","author":"Barber,","year":"2020"},{"key":"2023021111212402200_B2","author":"Barber,","year":"2020","journal-title":"The limits of distribution-free conditional predictive inference"},{"key":"2023021111212402200_B3","author":"Cand\u00e8s,","year":"2022","journal-title":"Conformalized survival analysis"},{"key":"2023021111212402200_B4","doi-asserted-by":"crossref","first-page":"e2107794118","DOI":"10.1073\/pnas.2107794118","article-title":"Distributional conformal prediction","volume":"118","author":"Chernozhukov,","year":"2021","journal-title":"Proc. Nat. Acad. Sci."},{"key":"2023021111212402200_B5","volume-title":"UCI Machine Learning Repository [http:\/\/archive.ics.uci.edu\/ml]","author":"Dua,","year":"2019"},{"key":"2023021111212402200_B6","author":"Feldman,","year":"2021","journal-title":"Calibrated multiple-output quantile regression with representation learning"},{"key":"2023021111212402200_B7","doi-asserted-by":"crossref","first-page":"524","DOI":"10.1111\/rssb.12443","article-title":"Prediction and outlier detection in classification problems","volume":"84","author":"Guan,","year":"2022","journal-title":"J. R. Statist. Soc. B"},{"key":"2023021111212402200_B8","doi-asserted-by":"crossref","first-page":"108496","DOI":"10.1016\/j.patcog.2021.108496","article-title":"Nested conformal prediction and quantile out-of-bag ensemble methods","volume":"127","author":"Gupta,","year":"2021","journal-title":"Pat. Recog."},{"key":"2023021111212402200_B9","author":"Hechtlinger,","year":"2019","journal-title":"Cautious deep learning"},{"key":"2023021111212402200_B10","author":"Izbicki,","year":"2019","journal-title":"Flexible distribution-free conditional predictive bands using density estimators"},{"key":"2023021111212402200_B11","first-page":"1589","article-title":"Quantile tomography: using quantiles with multivariate data","volume":"22","author":"Kong,","year":"2012","journal-title":"Statist. Sinica"},{"key":"2023021111212402200_B12","doi-asserted-by":"crossref","first-page":"1094","DOI":"10.1080\/01621459.2017.1307116","article-title":"Distribution-free predictive inference for regression","volume":"113","author":"Lei,","year":"2018","journal-title":"J. Am. Statist. Assoc."},{"key":"2023021111212402200_B13","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1007\/s10472-013-9366-6","article-title":"A conformal prediction approach to explore functional data","volume":"74","author":"Lei,","year":"2015","journal-title":"Ann. Math. Artif. Intel."},{"key":"2023021111212402200_B14","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1111\/rssb.12021","article-title":"Distribution-free prediction bands for non-parametric regression","volume":"76","author":"Lei,","year":"2014","journal-title":"J. R. Statist. Soc. B"},{"key":"2023021111212402200_B15","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.jmva.2010.08.004","article-title":"On directional multiple-output quantile regression","volume":"102","author":"Paindaveine,","year":"2011","journal-title":"J. Mult. Anal."},{"key":"2023021111212402200_B16","doi-asserted-by":"crossref","DOI":"10.1007\/3-540-36755-1_29","article-title":"Inductive confidence machines for regression","volume-title":"European Conference on Machine Learning","author":"Papadopoulos,","year":"2002"},{"key":"2023021111212402200_B17","first-page":"11pp","volume-title":"Conformalized quantile regression","author":"Romano,","year":"2019"},{"key":"2023021111212402200_B18","doi-asserted-by":"crossref","first-page":"e261","DOI":"10.1002\/sta4.261","article-title":"A comparison of some conformal quantile regression methods","volume":"9","author":"Sesia,","year":"2020","journal-title":"Stat"},{"key":"2023021111212402200_B19","first-page":"371","article-title":"A tutorial on conformal prediction","volume":"9","author":"Shafer,","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"2023021111212402200_B20","article-title":"Facebook comment volume prediction","volume":"16","author":"Singh","year":"2015","journal-title":"Int. J. Simul. Syst. Sci. Technol."},{"key":"2023021111212402200_B21","first-page":"15","volume-title":"Comment volume prediction using neural networks and decision trees","author":"Singh,","year":"2015"},{"key":"2023021111212402200_B22","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1007\/s10994-013-5355-6","article-title":"Conditional validity of inductive conformal predictors","volume":"92","author":"Vovk,","year":"2013","journal-title":"Mach. Learn"},{"key":"2023021111212402200_B23","volume-title":"Algorithmic Learning in a Random World","author":"Vovk,","year":"2005"},{"key":"2023021111212402200_B24","doi-asserted-by":"crossref","first-page":"1566","DOI":"10.1214\/08-AOS622","article-title":"On-line predictive linear regression","volume":"37","author":"Vovk,","year":"2009","journal-title":"Ann. Statist."},{"key":"2023021111212402200_B25","doi-asserted-by":"crossref","first-page":"1797","DOI":"10.1016\/S0008-8846(98)00165-3","article-title":"Modeling of strength of high-performance concrete using artificial neural networks","volume":"28","author":"Yeh,","year":"1998","journal-title":"Cem. Concr. Res."}],"container-title":["Biometrika"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/biomet\/advance-article-pdf\/doi\/10.1093\/biomet\/asac040\/45911782\/asac040.pdf","content-type":"application\/pdf","content-version":"am","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/biomet\/article-pdf\/110\/1\/33\/49160126\/asac040.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/biomet\/article-pdf\/110\/1\/33\/49160126\/asac040.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,11]],"date-time":"2023-02-11T11:22:26Z","timestamp":1676114546000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/biomet\/article\/110\/1\/33\/6647831"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,21]]},"references-count":25,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2022,7,21]]},"published-print":{"date-parts":[[2023,2,11]]}},"URL":"https:\/\/doi.org\/10.1093\/biomet\/asac040","relation":{},"ISSN":["0006-3444","1464-3510"],"issn-type":[{"value":"0006-3444","type":"print"},{"value":"1464-3510","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2023,3,1]]},"published":{"date-parts":[[2022,7,21]]}}}