{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T22:55:52Z","timestamp":1777157752604,"version":"3.51.4"},"reference-count":13,"publisher":"MIT Press - Journals","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Neural Computation"],"published-print":{"date-parts":[[2000,8,1]]},"abstract":"<jats:p> Knowledge about the distribution of a statistical estimator is important for various purposes, such as the construction of confidence intervals for model parameters or the determination of critical values of tests. A widely used method to estimate this distribution is the so-called bootstrap, which is based on an imitation of the probabilistic structure of the data-generating process on the basis of the information provided by a given set of random observations. In this article we investigate this classical method in the context of artificial neural networks used for estimating a mapping from input to output space. We establish consistency results for bootstrap estimates of the distribution of parameter estimates. <\/jats:p>","DOI":"10.1162\/089976600300015204","type":"journal-article","created":{"date-parts":[[2002,7,27]],"date-time":"2002-07-27T11:56:30Z","timestamp":1027770990000},"page":"1929-1949","source":"Crossref","is-referenced-by-count":53,"title":["Bootstrapping Neural Networks"],"prefix":"10.1162","volume":"12","author":[{"given":"J\u00fcrgen","family":"Franke","sequence":"first","affiliation":[{"name":"Department of Mathematics, University of Kaiserslautern, 67653 Kaiserslautern, Germany"}]},{"given":"Michael H.","family":"Neumann","sequence":"additional","affiliation":[{"name":"Department of Economics, Humboldt University of Berlin, 13591 Berlin, Germany"}]}],"member":"281","reference":[{"key":"p_1","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1995.7.3.624"},{"key":"p_3","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176344552"},{"key":"p_7","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176345638"},{"key":"p_10","doi-asserted-by":"publisher","DOI":"10.2307\/2288926"},{"key":"p_11","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1176349748"},{"key":"p_12","doi-asserted-by":"publisher","DOI":"10.1016\/0893-6080(89)90020-8"},{"key":"p_13","first-page":"429","volume":"308","author":"Huet S.","year":"1989","journal-title":"Acad. Sci. Paris Sr. I. Math."},{"key":"p_14","doi-asserted-by":"publisher","DOI":"10.1080\/02331889008802251"},{"key":"p_15","doi-asserted-by":"publisher","DOI":"10.1109\/72.329683"},{"key":"p_16","doi-asserted-by":"publisher","DOI":"10.1214\/aos\/1024691254"},{"key":"p_21","doi-asserted-by":"publisher","DOI":"10.2307\/2290076"},{"key":"p_22","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.425"},{"key":"p_23","doi-asserted-by":"publisher","DOI":"10.1016\/0893-6080(90)90004-5"}],"container-title":["Neural Computation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mitpressjournals.org\/doi\/pdf\/10.1162\/089976600300015204","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,3,12]],"date-time":"2021-03-12T21:47:56Z","timestamp":1615585676000},"score":1,"resource":{"primary":{"URL":"https:\/\/direct.mit.edu\/neco\/article\/12\/8\/1929-1949\/6396"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2000,8,1]]},"references-count":13,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2000,8,1]]}},"alternative-id":["10.1162\/089976600300015204"],"URL":"https:\/\/doi.org\/10.1162\/089976600300015204","relation":{},"ISSN":["0899-7667","1530-888X"],"issn-type":[{"value":"0899-7667","type":"print"},{"value":"1530-888X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2000,8,1]]}}}