Speaker
Prof.
Nikolay Gagunashvili
(University of Akureyri, Borgir, v/Nordurslod, IS-600 Akureyri, Iceland & Max-Planck-Institut f\"{u}r Kernphysik, P.O. Box 103980, 69029 Heidelberg, Germany)
Description
A mixture density model-based procedure for correcting experimental data for distortions due to finite resolution and limited detector acceptance is presented. The unfolding problem is known to be an ill-posed problem that can not be solved without some a priori information about the solution such as, for example, smoothness or positivity. In the approach presented here the true distribution is estimated by a weighted sum of densities, with the variances of the densities acting as a regularization parameter responsible for the smoothness of the result. Cross-validation is used to determine the optimal value of this parameter and a bootstrap method for estimation statistical errors of unfolded distribution. Numerical examples, one of them for a steeply falling probability density function, are presented to illustrate the procedure.
Primary author
Prof.
Nikolay Gagunashvili
(University of Akureyri, Borgir, v/Nordurslod, IS-600 Akureyri, Iceland & Max-Planck-Institut f\"{u}r Kernphysik, P.O. Box 103980, 69029 Heidelberg, Germany)
Co-author
Prof.
Michael Schmelling
(Max-Planck-Institut f\"{u}r Kernphysik, P.O. Box 103980, 69029 Heidelberg, Germany)
