{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,26]],"date-time":"2026-07-26T07:42:18Z","timestamp":1785051738681,"version":"3.55.0"},"reference-count":0,"publisher":"Cambridge University Press (CUP)","issue":"2","license":[{"start":{"date-parts":[[2000,4,1]],"date-time":"2000-04-01T00:00:00Z","timestamp":954547200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Econom. Theory"],"published-print":{"date-parts":[[2000,4]]},"abstract":"<jats:p>The autoregressive fractionally integrated moving \naverage (ARFIMA) model has become a popular approach for \nanalyzing time series that exhibit long-range dependence. \nFor the Gaussian case, there have been substantial advances \nin the area of likelihood-based inference, including development \nof the asymptotic properties of the maximum likelihood \nestimates and formulation of procedures for their computation. \nSmall-sample inference, however, has not to date been studied. \nHere we investigate the small-sample behavior of the conventional \nand Bartlett-corrected likelihood ratio tests (LRT) for \nthe fractional difference parameter. We derive an expression \nfor the Bartlett correction factor. We investigate the \nasymptotic order of approximation of the Bartlett-corrected \ntest. In addition, we present a small simulation study \nof the conventional and Bartlett-corrected LRT's. \nWe find that for simple ARFIMA models both tests perform \nfairly well with a sample size of 40 but the Bartlett-corrected \ntest generally provides an improvement over the conventional \ntest with a sample size of 20.<\/jats:p>","DOI":"10.1017\/s0266466600162048","type":"journal-article","created":{"date-parts":[[2002,7,27]],"date-time":"2002-07-27T13:47:49Z","timestamp":1027777669000},"page":"231-248","source":"Crossref","is-referenced-by-count":5,"title":["SMALL-SAMPLE LIKELIHOOD-BASED INFERENCE IN THE ARFIMA MODEL"],"prefix":"10.1017","volume":"16","author":[{"given":"Offer","family":"Lieberman","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Judith","family":"Rousseau","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"David M.","family":"Zucker","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2000,4,1]]},"container-title":["Econometric Theory"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0266466600162048","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,2]],"date-time":"2019-04-02T19:23:49Z","timestamp":1554233029000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0266466600162048\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2000,4]]},"references-count":0,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2000,4]]}},"alternative-id":["S0266466600162048"],"URL":"https:\/\/doi.org\/10.1017\/s0266466600162048","relation":{},"ISSN":["0266-4666","1469-4360"],"issn-type":[{"value":"0266-4666","type":"print"},{"value":"1469-4360","type":"electronic"}],"subject":[],"published":{"date-parts":[[2000,4]]}}}