Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/55596
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dc.contributor.authorHung T. Nguyenen_US
dc.date.accessioned2018-09-05T02:58:18Z-
dc.date.available2018-09-05T02:58:18Z-
dc.date.issued2016-01-01en_US
dc.identifier.issn16113349en_US
dc.identifier.issn03029743en_US
dc.identifier.other2-s2.0-85006054188en_US
dc.identifier.other10.1007/978-3-319-49046-5_1en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85006054188&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/55596-
dc.description.abstract© Springer International Publishing AG 2016. In view of the recent ban of the use of P-values in statistical inference, since they are not qualified as information measures of support from empirical evidence, we will not only take a closer look at them, but also embark on a panorama of more promising ingredients which could replace P-values for statistical science as well as for any fields involving reasoning with integrated uncertainty. These ingredients include the recently developed theory of Inferential Models, the emergent Information Theoretic Statistics, and of course Bayesian statistics. The lesson learned from the ban of P-values is emphasized for other types of uncertainty measures, where information measures, their logical aspects (conditional events, probability logic) are examined.en_US
dc.subjectComputer Scienceen_US
dc.subjectMathematicsen_US
dc.titleOn evidential measures of support for reasoning with integrated uncertainty: A lesson from the ban of P-values in statistical inferenceen_US
dc.typeBook Seriesen_US
article.title.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
article.volume9978 LNAIen_US
article.stream.affiliationsNew Mexico State University Las Crucesen_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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