Bayesian methodsBayesian / computational
动态蒙特卡洛模拟
动态蒙特卡洛（DMC）模拟是一种计算方法，通过抽取由跃迁率加权的随机事件序列来跟踪系统的随机时间演化。与静态蒙特卡洛采样平衡分布不同，DMC明确地推进时钟，使其适用于事件的顺序和时序很重要的动力学、反应和时间相关现象。
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The neighbourhood of related methods — select a node to explore.
来源
- Bortz, A. B., Kalos, M. H., & Lebowitz, J. L. (1975). A new algorithm for Monte Carlo simulation of Ising spin systems. Journal of Computational Physics, 17(1), 10–18. DOI: 10.1016/0021-9991(75)90060-1 ↗
- Gillespie, D. T. (1977). Exact stochastic simulation of coupled chemical reactions. The Journal of Physical Chemistry, 81(25), 2340–2361. DOI: 10.1021/j100540a008 ↗
如何引用本页
ScholarGate. (2026, June 3). Dynamic Monte Carlo Simulation. ScholarGate. https://scholargate.app/zh/bayesian/dynamic-monte-carlo-simulation
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
- 自助法模拟仿真↔ compare
- 动态贝叶斯推断贝叶斯↔ compare
- Gibbs Sampling贝叶斯↔ compare
- 马尔可夫链蒙特卡洛 (MCMC)仿真↔ compare
- 粒子滤波器（序贯蒙特卡洛）贝叶斯↔ compare
- 顺序蒙特卡洛贝叶斯↔ compare