Foundations of Bayesianism /
Foundations of Bayesianism is an authoritative collection of papers addressing the key challenges that face the Bayesian interpretation of probability today. Some of these papers seek to clarify the relationships between Bayesian, causal and logical reasoning. Others consider the application of Baye...
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| Format: | eBook |
| Language: | English |
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Dordrecht :
Springer Netherlands,
2001.
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| Series: | Applied logic series ;
24. |
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| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Editorial Foreword
- Editorial Preface
- Introduction: Bayesianism into the 21st Century
- Bayesianism, Causality and Networks. Bayesianism and Causality, or, Why I am only a Half-Bayesian. Causal Inference without Counterfactuals. Foundations for Bayesian Networks. Probabilistic Learning Models
- Logic, Mathematics and Bayesianism. The Logic of Bayesian Probability. Subjectivism, Objectivism and Objectivity in Bruno de Finetti's Bayesianism. Bayesianism in Mathematics. Common Sense and Stochastic Independence. Integrating Probabilistic and Logical Reasoning
- Bayesianism and Decision Theory. Ramsey and the Measurement of Belief. Bayesianism and Independence. The Paradox of the Bayesian Experts
- Criticisms of Bayesianism. Bayesian Learning and Expectations Formation: Anything Goes. Bayesianism and the Fixity of the Theoretical Framework. Principles of Inference and their Consequences
- Index.