期刊全稱 | Bayesian Inference and Maximum Entropy Methods in Science and Engineering | 期刊簡稱 | MaxEnt 37, Jarinu, B | 影響因子2023 | Adriano Polpo,Julio Stern,Hellinton Takada | 視頻video | http://file.papertrans.cn/182/181850/181850.mp4 | 發(fā)行地址 | Presents cutting-edge research from a wide variety of science and engineering fields that use inductive statistics.Examines and discusses the foundations of inductive statistics, addressing the growin | 學(xué)科分類 | Springer Proceedings in Mathematics & Statistics | 圖書封面 |  | 影響因子 | .These proceedings from the 37th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2017), held in S?o Carlos, Brazil, aim to expand the available research on Bayesian methods and promote their application in the scientific community. They gather research from scholars in many different fields who use inductive statistics methods and focus on the foundations of the Bayesian paradigm, their comparison to objectivistic or frequentist statistics counterparts, and their appropriate applications.?..Interest in the foundations of inductive statistics has been growing with the increasing availability of Bayesian methodological alternatives, and scientists now face much more difficult choices in finding the optimal methods to apply to their problems. By carefully examining and discussing the relevant foundations, the scientific community can avoid applying Bayesian methods on a merely ad hoc basis.?.For over 35 years, the MaxEnt workshops have explored the use of Bayesian and Maximum Entropy methods in scientific and engineering application contexts. The workshops welcome contributions on all aspects of probabilistic inference, inclu | Pindex | Conference proceedings 2018 |
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