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- Title
Learning and Pooling, Pooling and Learning.
- Authors
Stewart, Rush T.; Quintana, Ignacio Ojea
- Abstract
We explore which types of probabilistic updating commute with convex IP pooling (Stewart and Ojea Quintana <xref>2017</xref>). Positive results are stated for Bayesian conditionalization (and a mild generalization of it), imaging, and a certain parameterization of Jeffrey conditioning. This last observation is obtained with the help of a slight generalization of a characterization of (precise) externally Bayesian pooling operators due to Wagner (Log J IGPL 18(2):336-345, <xref>2009</xref>). These results strengthen the case that pooling should go by imprecise probabilities since no precise pooling method is as versatile.
- Subjects
CONDITIONAL probability; PROBABILITY theory; PUBLIC opinion polls; LEARNING; CONTINUOUS probability theory
- Publication
Erkenntnis, 2018, Vol 83, Issue 3, p369
- ISSN
0165-0106
- Publication type
Article
- DOI
10.1007/s10670-017-9894-2