论文标题
贝叶斯功能仿真对未来气候变化方案的二氧化碳排放量
Bayesian Functional Emulation of CO2 Emissions on Future Climate Change Scenarios
论文作者
论文摘要
我们根据功能回归框架提出了一个气候经济确定性综合评估模型集合的统计模拟器。对未知参数的推断是通过混合效应分层模型使用完全贝叶斯框架进行的，在所有参数的向量上都有先验分布。我们还建议对误差的协方差矩阵进行自回归参数化，并具有匹配的边缘先验。通过这种方式，我们允许使用模拟器离散输出的功能框架，以允许其时间连续评估。
We propose a statistical emulator for a climate-economy deterministic integrated assessment model ensemble, based on a functional regression framework. Inference on the unknown parameters is carried out through a mixed effects hierarchical model using a fully Bayesian framework with a prior distribution on the vector of all parameters. We also suggest an autoregressive parameterization of the covariance matrix of the error, with matching marginal prior. In this way, we allow for a functional framework for the discretized output of the simulators that allows their time continuous evaluation.
