{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T23:11:28Z","timestamp":1680390688338},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"4","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2014,12,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>The uncertainty of world population growth represents a serious global problem. Existing methods for quantifying this uncertainty face a variety of questions. An essential problem of these methods is the lack of direct evidence for their validity, for example by means of comparisons with independent observations like measurements. A way to support the validity of such forecast methods is to validate these models with reference models, which play the role of independent observations. Desired properties of such a reference model are formulated here. A new reference world population model is formulated by a probabilistic extension of recent deterministic UN projections. This model is validated in terms of theory and observations: it is shown that the model has all desired properties of a reference model, and its predictions are very well supported by the known world population development from 1980 till 2010. Applications of this model as a reference model demonstrate the advantages of the stochastic world population model presented here.<\/jats:p>","DOI":"10.1515\/mcma-2014-0005","type":"journal-article","created":{"date-parts":[[2014,12,2]],"date-time":"2014-12-02T18:16:29Z","timestamp":1417544189000},"page":"261-277","source":"Crossref","is-referenced-by-count":0,"title":["Uncertainty quantification of world population growth: A self-similar PDF model"],"prefix":"10.1515","volume":"20","author":[{"given":"Stefan","family":"Heinz","sequence":"first","affiliation":[{"name":"Department of Mathematics, University of Wyoming, 1000 East University Avenue, Laramie, WY 82071, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"374","published-online":{"date-parts":[[2014,10,31]]},"container-title":["Monte Carlo Methods and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mcma-2014-0005\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mcma-2014-0005\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T22:35:54Z","timestamp":1680388554000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/mcma-2014-0005\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,10,31]]},"references-count":0,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2014,9,13]]},"published-print":{"date-parts":[[2014,12,1]]}},"alternative-id":["10.1515\/mcma-2014-0005"],"URL":"https:\/\/doi.org\/10.1515\/mcma-2014-0005","relation":{},"ISSN":["0929-9629","1569-3961"],"issn-type":[{"value":"0929-9629","type":"print"},{"value":"1569-3961","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,10,31]]}}}