A new method to unfold experimental event distributions is presented. Monte Carlo simulated events are weighted iteratively in such a way that the distribution of the undistorted variables of the simulated events approximates the undistorted experimental distribution. The method is binning free, applicable to multivariate problems and easy to use. It is illustrated with a simple example and compared to a least square method with regularization.
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Univ Calif Los Angeles, Interdivis Program Stat, Los Angeles, CA 90095 USAUniv Calif Los Angeles, Interdivis Program Stat, Los Angeles, CA 90095 USA
Wong, WH
Liang, FM
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Univ Calif Los Angeles, Interdivis Program Stat, Los Angeles, CA 90095 USAUniv Calif Los Angeles, Interdivis Program Stat, Los Angeles, CA 90095 USA