Bayesian methodsBayesian / computational
时间序列近似贝叶斯计算
时间序列ABC是一种无似然的贝叶斯推断方法，通过比较模拟轨迹的汇总统计量与观测序列的汇总统计量来估计动力学或时间索引系统的模型参数的后验分布，从而绕开了评估解析似然函数的需要。它对于似然函数难以处理的复杂机理模型或随机模型尤其有价值。
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Method map
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来源
- Toni, T., Welch, D., Strelkowa, N., Ipsen, A. & Stumpf, M. P. H. (2009). Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems. Journal of the Royal Society Interface, 6(31), 187–202. DOI: 10.1098/rsif.2008.0172 ↗
- Sisson, S. A., Fan, Y. & Beaumont, M. A. (Eds.) (2018). Handbook of Approximate Bayesian Computation. CRC Press. ISBN: 978-1439881507
如何引用本页
ScholarGate. (2026, June 3). Time Series Approximate Bayesian Computation. ScholarGate. https://scholargate.app/zh/bayesian/time-series-approximate-bayesian-computation
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.
- 近似贝叶斯计算仿真↔ compare
- 动态贝叶斯推断贝叶斯↔ compare
- 卡尔曼滤波器贝叶斯↔ 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
- 时间序列贝叶斯推断贝叶斯↔ compare