{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,13]],"date-time":"2026-02-13T17:00:30Z","timestamp":1771002030491,"version":"3.50.1"},"reference-count":0,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[1999,11,1]],"date-time":"1999-11-01T00:00:00Z","timestamp":941414400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[1999,11,1]]},"abstract":"<jats:title>Summary<\/jats:title>\n               <jats:p>It is widely known that bootstrap failure can often be remedied by using a technique known as the \u2018m out of n\u2019 bootstrap, by which a smaller number, m say, of observations are resampled from the original sample of size n. In successful cases of the bootstrap, the m out of n bootstrap is often deemed unnecessary. We show that the problem of constructing nonparametric confidence intervals is an exceptional case. By considering a new class of m out of n bootstrap confidence limits, we develop a computationally efficient approach based on the double bootstrap to construct the optimal m out of n bootstrap intervals. We show that the optimal intervals have a coverage accuracy which is comparable with that of the classical double-bootstrap intervals, and we conduct a simulation study to examine their performance. The results are in general very encouraging. Alternative approaches which yield even higher order accuracy are also discussed.<\/jats:p>","DOI":"10.1111\/1467-9868.00209","type":"journal-article","created":{"date-parts":[[2003,3,12]],"date-time":"2003-03-12T19:35:56Z","timestamp":1047497756000},"page":"901-911","source":"Crossref","is-referenced-by-count":17,"title":["On a Class of <i>m<\/i> out of <i>n<\/i> Bootstrap Confidence Intervals"],"prefix":"10.1093","volume":"61","author":[{"given":"Stephen M. S.","family":"Lee","sequence":"first","affiliation":[{"name":"University of Hong Kong , Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2002,1,6]]},"container-title":["Journal of the Royal Statistical Society Series B: Statistical Methodology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1111%2F1467-9868.00209","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/academic.oup.com\/jrsssb\/article-pdf\/61\/4\/901\/49589595\/jrsssb_61_4_901.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/jrsssb\/article-pdf\/61\/4\/901\/49589595\/jrsssb_61_4_901.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,3,22]],"date-time":"2023-03-22T06:57:46Z","timestamp":1679468266000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/jrsssb\/article\/61\/4\/901\/7083200"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[1999,11,1]]},"references-count":0,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2002,1,6]]},"published-print":{"date-parts":[[1999,11,1]]}},"URL":"https:\/\/doi.org\/10.1111\/1467-9868.00209","relation":{},"ISSN":["1369-7412","1467-9868"],"issn-type":[{"value":"1369-7412","type":"print"},{"value":"1467-9868","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[1999,11]]},"published":{"date-parts":[[1999,11,1]]}}}