Bayesian methodsBayesian / computational
空间马尔可夫链蒙特卡洛 (Spatial MCMC)
空间马尔可夫链蒙特卡洛 (Spatial MCMC) 将马尔可夫链蒙特卡洛采样应用于明确考虑观测值之间空间依赖性的贝叶斯模型。它从条件自回归 (CAR)、同步自回归 (SAR) 或地统计学 (高斯过程) 模型等模型中抽取后验样本，从而获得具有空间结构参数（如随机效应、回归系数和空间范围）的完整不确定性分布。
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来源
- Banerjee, S., Carlin, B. P., & Gelfand, A. E. (2015). Hierarchical Modeling and Analysis for Spatial Data (2nd ed.). CRC Press. ISBN: 978-1439819173
- Rue, H., & Held, L. (2005). Gaussian Markov Random Fields: Theory and Applications. CRC Press. ISBN: 978-1584884323
如何引用本页
ScholarGate. (2026, June 3). Markov Chain Monte Carlo for Spatial Models. ScholarGate. https://scholargate.app/zh/bayesian/spatial-mcmc
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