{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T17:31:44Z","timestamp":1774891904543,"version":"3.50.1"},"reference-count":0,"publisher":"World Scientific Pub Co Pte Lt","issue":"06","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Unc. Fuzz. Knowl. Based Syst."],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:p> Uncertain time series analysis is a method to predict future values based on imprecisely observed values. As a basic model of uncertain time series, an uncertain autoregressive model has been presented. However, the existing paper ignores the temporal dependence information embedded in time-series data. In dealing with this issue, this paper adds a least absolute shrinkage and selection operator penalty to the traditional uncertain autoregressive model and selects the optimum order of the model according to Akaike\u2019s final prediction error criterion. Finally, two numerical examples are given to illustrate the effectiveness of the model and compare the results predicted by the uncertain autoregressive model with the principle of least squares. <\/jats:p>","DOI":"10.1142\/s0218488520500415","type":"journal-article","created":{"date-parts":[[2020,11,2]],"date-time":"2020-11-02T07:42:15Z","timestamp":1604302935000},"page":"939-956","source":"Crossref","is-referenced-by-count":33,"title":["Uncertain Autoregressive Model via LASSO Procedure"],"prefix":"10.1142","volume":"28","author":[{"given":"Ziqian","family":"Zhang","sequence":"first","affiliation":[{"name":"School of Information Technology and Management, University of International Business and Economics, Beijing 100029, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiangfeng","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Information Technology and Management, University of International Business and Economics, Beijing 100029, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinwu","family":"Gao","sequence":"additional","affiliation":[{"name":"School of Economics, Ocean University of China, Qingdao 266100, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2020,11,25]]},"container-title":["International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218488520500415","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,11,30]],"date-time":"2020-11-30T05:48:24Z","timestamp":1606715304000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218488520500415"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,25]]},"references-count":0,"journal-issue":{"issue":"06","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["10.1142\/S0218488520500415"],"URL":"https:\/\/doi.org\/10.1142\/s0218488520500415","relation":{},"ISSN":["0218-4885","1793-6411"],"issn-type":[{"value":"0218-4885","type":"print"},{"value":"1793-6411","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,25]]}}}