Bayesian methodsBayesian / computational
带测量误差的近似贝叶斯计算
带测量误差的近似贝叶斯计算（ABC-ME）将标准ABC无似然框架扩展到观测数据本身具有噪声或记录不精确的场景。通过在接受步骤中明确纳入测量误差核，ABC-ME即使在无法直接观测真实数据生成过程的情况下，也能针对模型参数的正确后验分布。
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Method map
The neighbourhood of related methods — select a node to explore.
来源
- Wilkinson, R. D. (2013). Approximate Bayesian computation (ABC) gives exact results under the assumption of model error. Statistical Applications in Genetics and Molecular Biology, 12(2), 129-141. DOI: 10.1515/sagmb-2013-0010 ↗
- Beaumont, M. A. (2010). Approximate Bayesian computation in evolution and ecology. Annual Review of Ecology, Evolution, and Systematics, 41, 379-406. DOI: 10.1146/annurev-ecolsys-102209-144621 ↗
如何引用本页
ScholarGate. (2026, June 3). Approximate Bayesian Computation with Measurement Error. ScholarGate. https://scholargate.app/zh/bayesian/approximate-bayesian-computation-with-measurement-error
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
- 带有测量误差的贝叶斯推断贝叶斯↔ compare
- 含测量误差的MCMC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