Accelerate Monte Carlo Simulation for Probability Measures by an Interrupt Mechanism

Monte Carlo simulation (MCS) is useful for verifying analytical derivations and studying complex systems on an empirical basis. Although MCS straightforward does not require a priori knowledge of the sampled probability measures (PMs), it consumes tremendous amount computational resource suffers from slow procedures sophisticated systems. To mitigate this drawback MCS, we make full use monotone property logarithmic presentation convention PMs in regard to power related metrics (PRMs) communications science propose easy-to-implement interrupt mechanism accelerate estimating PMs. facilitate programming different platforms provide solid theoretical foundation, present generic implementation framework suited with certain properties by analyze underlying theory mechanism. In particular, apply de Moivre-Laplace theorem analytic continuation prove asymptotic consistency under indirect setup MCS. We also design hypothesis test proposed statistical