Abstract
In §5 we discussed two ways in which classical statistics can be captured in Schema (1.1),, one using functional models and fiducial probability, and one using evidential probability to represent the fiducial argument. This section investigates the use of the common machinery of §8.2 and Algorithm 7 in classical statistics.
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References
Seidenfeld, T. (1979). Philosophical Problems of Statistical Inference: Learning from R.A. Fisher. Reidel, Dordrecht.
Seidenfeld, T. (1992). R. A. Fisher’s fiducial argument and Bayes’ theorem. Statistical Science, 7:358–368.
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© 2011 Springer Science+Business Media B.V.
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Haenni, R., Romeijn, JW., Wheeler, G., Williamson, J. (2011). Networks for Statistical Inference. In: Probabilistic Logics and Probabilistic Networks. Synthese Library, vol 350. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0008-6_12
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DOI: https://doi.org/10.1007/978-94-007-0008-6_12
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