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Title: The Bayesian Cost–Effectiveness Decision Problem
Authors: Moreno, Elias
Vázquez-Polo, Francisco José 
Negrín, Miguel 
Martel-Escobar, María 
UNESCO Clasification: 330416 Diseño lógico
120304 Inteligencia artificial
1208 Probabilidad
Keywords: Bayesian method
Issue Date: 2017
Publisher: Springer 
Journal: Decisions in Economics and Finance 
Conference: 14th International Conference on Distributed Computing and Artificial Intelligence, DCAI 2017 
Abstract: The proceedings contain 16 papers. The special focus in this conference is on Distributed Computing and Artificial Intelligence. The topics include: The Bayesian cost–effectiveness decision problem; evaluation of scientific production without using bibliometric indicators; information aggregation in big data; a decision framework for understanding data-aware business process models; cluster analysis as a decision-making tool; similar patterns of cultural and creative industries; a basic algorithm to support decision-making behaviour; looking for regional convergence; information manipulation and web credibility; a data mining analysis of the Chinese inland-coastal inequality; a unified framework for multicriteria evaluation of intangible capital assets inside organizations; processing and analysing experimental data using a tensor-based method and the mediating effect of the absorptive capacity in the international entrepreneurial orientation of family firms.
ISBN: 9783319608815
ISSN: 1593-8883
DOI: 10.1007/978-3-319-60882-2_1
Source: Moreno E., Vázquez–Polo FJ., Negrín M.A., Martel–Escobar M. (2018) The Bayesian Cost–Effectiveness Decision Problem. In: Bucciarelli E., Chen SH., Corchado J. (eds) Decision Economics: In the Tradition of Herbert A. Simon's Heritage. DCAI 2017. Advances in Intelligent Systems and Computing, vol 618. Springer, Cham
Appears in Collections:Actas de congresos
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