Process / pipelineSimulation / optimization
贝叶斯马尔可夫模型 — 状态转移建模与贝叶斯参数估计
贝叶斯马尔可夫模型是一种状态转移模拟方法，它将马尔可夫链队列模型与贝叶斯统计推断相结合。通过对转移概率设定先验分布并用观测数据更新它们，该方法将完整的参数不确定性传播到整个模拟过程中，从而产生关于成本、生命年或质量调整生命年等结果的后验分布，而不是单点估计。
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
Method map
The neighbourhood of related methods — select a node to explore.
来源
- Briggs, A., Sculpher, M., Claxton, K. (2006). Decision Modelling for Health Economic Evaluation. Oxford University Press, Oxford. ISBN: 9780198526629
- Jackson, C. H., Sharples, L. D., Thompson, S. G. (2010). Structural and parameter uncertainty in Bayesian cost-effectiveness models. Journal of the Royal Statistical Society: Series C (Applied Statistics), 59(2), 233-253. DOI: 10.1111/j.1467-9876.2009.00684.x ↗
如何引用本页
ScholarGate. (2026, June 3). Bayesian Markov Model — State-Transition Modeling with Bayesian Parameter Estimation. ScholarGate. https://scholargate.app/zh/simulation/bayesian-markov-model
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.
Compare side by side →