1-5 September 2014
Faculty of Civil Engineering
Europe/Prague timezone

Densities mixture unfolding for data obtained from detectors with finite resolution and limited acceptance

2 Sep 2014, 14:25
25m
C219 (Faculty of Civil Engineering)

C219

Faculty of Civil Engineering

Faculty of Civil Engineering, Czech Technical University in Prague Thakurova 7/2077 Prague 166 29 Czech Republic
Oral Data Analysis - Algorithms and Tools Data Analysis - Algorithms and Tools

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)

Presentation Materials