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The book explores a frequentist approach to conditionalization on partially known events through the concept of probability testbeds, offering a generalization of classical conditional probability. It introduces frequentist partial (F.P.) conditionalization and examines it in relation to partitions, segmentation, independence, and chaining. Notably, F.P. conditionalization extends Jeffrey conditionalization to arbitrary event collections, providing a new perspective and potential applications. Additionally, it presents a counterpart to Jeffrey's rule concerning independent updates, enhancing the understanding of these concepts.
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Generalized Jeffrey Conditionalization, Dirk Draheim
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- 2017
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