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A kernel based procedure for correcting experimental data for distortions dueto the finite resolution and limited detector acceptance is presented. Theunfolding problem is known to be an ill-posed problem that can not be solvedwithout some a priori information about solution such as, for example,smoothness or positivity. In the approach presented here the true distributionis estimated by a weighted sum of kernels, with the width of the kernels actingas a regularization parameter responsible for the smoothness of the result.Cross-validation is used to determine an optimal value for this parameter. Anumerical example with a simulation study of systematical and statisticalerrors is presented to illustrate the procedure.

Kernel based unfolding of data obtained from detectors with finite resolution and limited acceptance