The weighted stochastic simulation algorithm (wSSA) recently developed by Kuwahara and Mura and the refined\r\nwSSA proposed by Gillespie et al. based on the importance sampling technique open the door for efficient\r\nestimation of the probability of rare events in biochemical reaction systems. In this paper, we first apply the\r\nimportance sampling technique to the next reaction method (NRM) of the stochastic simulation algorithm and\r\ndevelop a weighted NRM (wNRM). We then develop a systematic method for selecting the values of importance\r\nsampling parameters, which can be applied to both the wSSA and the wNRM. Numerical results demonstrate that\r\nour parameter selection method can substantially improve the performance of the wSSA and the wNRM in terms\r\nof simulation efficiency and accuracy.
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