Abstract
Conditional Monte Carlo has been recognized as a potentially useful method in various Monte Carlo applications. It seems, however, that the method has not gained widespread popularity, presumably due to the complexity involved in the formulation and operation of the technique. We present herein what we believe to be an original and simplified approach to conditional Monte Carlo interpreting it as a modified form of importance sampling. This provides a straightforward framework by which any conditional sampling problem can be handled. The benefits are demonstrated by applying our approach to two problems; one of a general statistical nature and the other concerning the neutron transport equation.
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