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随机马尔可夫模型 — 具有不确定性传播的概率状态转移模拟

随机马尔可夫模型 (Stochastic Markov Model) 是一种模拟技术，它将一个系统表示为一组互斥的健康或决策状态，通过概率抽样的转移参数将一群（或个体代理）在这些状态之间移动，并通过数千次蒙特卡洛迭代来汇总结果，从而产生成本、结果或排序的完整概率分布，而不是单一的点估计。

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随机马尔可夫模型
离散事件仿真 (DES)马尔可夫模型个体模拟蒙特卡洛模拟敏感性分析随机动态规划Agent-Based Markov Model贝叶斯马尔可夫模型确定性马尔可夫模型多目标马尔可夫模型

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来源

  1. Sonnenberg, F. A., & Beck, J. R. (1993). Markov models in medical decision making: A practical guide. Medical Decision Making, 13(4), 322–338. DOI: 10.1177/0272989X9301300409 ↗
  2. Briggs, A., Sculpher, M., & Claxton, K. (2006). Decision Modelling for Health Economic Evaluation. Oxford University Press. ISBN: 9780198526629

如何引用本页

ScholarGate. (2026, June 3). Stochastic Markov Model — Probabilistic State-Transition Simulation with Uncertainty Propagation. ScholarGate. https://scholargate.app/zh/simulation/stochastic-markov-model

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被引用于

Agent-Based Markov Model贝叶斯马尔可夫模型确定性马尔可夫模型马尔可夫模型多目标马尔可夫模型稳健马尔可夫模型随机微观模拟随机排队模拟Stochastic Sensitivity Analysis

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ScholarGate — Stochastic Markov Model (Stochastic Markov Model — Probabilistic State-Transition Simulation with Uncertainty Propagation). 于 2026-06-15 检索自 https://scholargate.app/zh/simulation/stochastic-markov-model · 数据集： https://doi.org/10.5281/zenodo.20539026