Fully Bayesian Unfolding

Bayesian inference is applied directly to the problem of unfolding. The outcome is a posterior probability density for the spectrum before smearing, defined in the multi-dimensional space of all possible spectra. Regularization consists in choosing a non-constant prior. Despite some similarity, the fully bayesian unfolding (FBU) method, presented here, should not be confused with D'Agostini's iterative method.