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DC Field | Value | Language |
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dc.contributor.author | Hung T. Nguyen | en_US |
dc.contributor.author | Nguyen Duc Trung | en_US |
dc.contributor.author | Nguyen Ngoc Thach | en_US |
dc.date.accessioned | 2019-08-05T04:35:14Z | - |
dc.date.available | 2019-08-05T04:35:14Z | - |
dc.date.issued | 2019-01-01 | en_US |
dc.identifier.issn | 1860949X | en_US |
dc.identifier.other | 2-s2.0-85065610990 | en_US |
dc.identifier.other | 10.1007/978-3-030-04200-4_1 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85065610990&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/65551 | - |
dc.description.abstract | © Springer Nature Switzerland AG 2019. We elaborate on various uncertainty calculi in current research efforts to improve empirical econometrics. These consist essentially of considering appropriate non additive (and non commutative) probabilities, as well as taking into account economic data which involved economic agents’ behavior. After presenting a panorama of well-known non traditional probabilistic methods, we focus on the emerging effort of taking the analogy of financial econometrics with quantum mechanics to exhibit the promising use of quantum probability for modeling human behavior, and of Bohmian mechanics for modeling economic data. | en_US |
dc.subject | Computer Science | en_US |
dc.title | Beyond traditional probabilistic methods in econometrics | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Studies in Computational Intelligence | en_US |
article.volume | 809 | en_US |
article.stream.affiliations | Vietnam National University Ho Chi Minh City | en_US |
article.stream.affiliations | New Mexico State University Las Cruces | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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