| 书目名称 | Generalized Jeffrey Conditionalization | | 副标题 | A Frequentist Semant | | 编辑 | Dirk Draheim | | 视频video | | | 概述 | Provides a frequentist semantics for conditionalization on partially known events.Analyzes the resulting partial conditionalization with respect to partitions, segmentation, independence, chaining, an | | 丛书名称 | SpringerBriefs in Computer Science | | 图书封面 |  | | 描述 | This book provides a frequentist semantics for conditionalization on partially known events, which is given as a straightforward generalization of classical conditional probability via so-called probability testbeds. It analyzes the resulting partial conditionalization, called frequentist partial (F.P.) conditionalization, from different angles, i.e., with respect to partitions, segmentation, independence, and chaining. It turns out that F.P. conditionalization meets and generalizes Jeffrey conditionalization, i.e., from partitions to arbitrary collections of events, opening it for reassessment and a range of potential applications. A counterpart of Jeffrey’s rule for the case of independence holds in our frequentist semantics. This result is compared to Jeffrey’s commutative chaining of independent updates..The postulate of Jeffrey‘s probability kinematics, which is rooted in the subjectivism of Frank P. Ramsey, is found to be a consequence in our frequentist semantics. This way the book creates a link between the Kolmogorov system of probability and one of the important Bayesian frameworks. Furthermore, it shows a preservation result for conditional probabilities under the full u | | 出版日期 | Book 2017 | | 关键词 | Probability and Statistics; Logic; Knowledge Representation and Reasoning; Decision Support Systems; Com | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-69868-7 | | isbn_softcover | 978-3-319-69867-0 | | isbn_ebook | 978-3-319-69868-7Series ISSN 2191-5768 Series E-ISSN 2191-5776 | | issn_series | 2191-5768 | | copyright | The Author(s) 2017 |
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发表于 2025-3-21 18:34:07
