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This paper reviews the basic ideas behind a Bayesian unfolding published some years ago and improves their implementation.
International Organization for Standardization (ISO), “Guide to the expression of uncertainty in measurement”
1993
Earlier work this paper cites.
M. Nakao, Measurement of the proton structure function F 2 F_{2} at HERA
1994
Earlier work this paper cites.
G. D’Agostini, A multidimensional unfolding method based on Bayes’ theorem
1995
Earlier work this paper cites.
M. Raso, A measurement of the σ e p \sigma_{e\,p} for Q 2 < 0.3 Q^{2}<0.3\, GeV 2 , as a by product of the F 2 e p F_{2}^{ep} measurement
1998
Cited alongside, same era.
G. D’Agostini, Bayesian reasoning in data analysis: A critical intro
2003
Cited alongside, same era.
G. D’Agostini, Fits, and especially linear fits, with errors on both axes, extra variance of the data points and other complications
Cited in the paper.
G. D’Agostini, Asymmetric uncertainties: sources, treatment and possible dangers
Cited in the paper.
http://www.roma1.infn.it/~dagos/prob+stat.html#unf2
Cited in the paper.
G. D’Agostini, Bayesian inference in processing experimental data: principles and basic applications
2003
Later among the works it cites.
R Development Core Team (2009) R: A language and environment for statistical computing. R Foundation for Statistical Computing
2009
Later among the works it cites.
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