The conventional non-analogous Monte Carlo methods are optimized to preserve the mean value of the distributions and is therefore not suited for non-Boltzmann problems like the estimation of coincidences of correlation. This paper presents a general method called history splitting for the non-analogous estimation of such quantities. Calculations with a simple Monte Carlo program for a pulse-height-type estimator prove that the method is feasible and provides unbiased estimation. Different variance reduction techniques have been tried with the method and Russian roulette turned out to be ineffective in high multiplicity systems. Alternative history control methods are applied instead. Simulation results of a Feynman-a measurement shows that even the reconstruction of the higher moments is possible with the history splitting method, which makes feasible the simulation of neutron noise measurements.

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