Understand
Two different techniques for adding additional data sets to existing global fits using Bayesian reweighting have been proposed in the literature.
- The derivation of each reweighting formalism is critically reviewed.
- A simple example is constructed that conclusively favors one of the two formalisms.
- The effects of this choice for global fits is discussed.
Built on
D.T. Gillespie, “A theorem for physicists in the theory of random variables”, Am. J. Phys. 51
1983
Earlier work this paper cites.
W. T. Giele and S. Keller, Phys. Rev. D 58
1998
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2012
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J.M. Bernardo, http://www.uv.es/~bernardo/teaching.html
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2012
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