论文标题
使用JAGS/RJAGS应用于K $^{\ PM} $质量确定的实验结果的持怀疑态度组合
Skeptical combination of experimental results using JAGS/rjags with application to the K$^{\pm}$ mass determination
论文作者
论文摘要
几年前在上一篇论文中详细处理了“看起来”与“看起来”相互分歧的实验结果的问题。本注释的第一个新颖性是明确使用图形模型，以使目标变量之间的确定性和概率联系更为明显。然后，与其瞄准封闭公式的结果，不如通过{\ em Markov链Monte Carlo}（MCMC）采样评估了感兴趣的积分，并在软件包JAGS中实现了算法（通常是Gibbs Sampler）（“只是另一个Gibbs Sampler”）。为了方便起见，jags函数是从r脚本调用的，因此获得了R安装中包含的数学，统计和图形功能的丰富集合获得的优势。因此，前一篇论文的结果很容易重新验证，该方法应用于带电的Kaon质量的测定。本说明，基于博士学位学生和年轻研究人员的讲座，已经用教学触摸编写，并提供了相关的JAGS/RJAGS代码。 （由$ \ sqrt {χ^2/ν} $缩放处方的顺序应用引起的奇怪偏见，此处发现，将在此处发现的“显然不差”结果进行详细讨论。）
The question of how to combine experimental results that `appear' to be in mutual disagreement, treated in detail years ago in a previous paper, is revisited. The first novelty of the present note is the explicit use of graphical models, in order to make the deterministic and probabilistic links between the variables of interest more evident. Then, instead of aiming for results in closed formulae, the integrals of interest are evaluated by {\em Markov Chain Monte Carlo} (MCMC) sampling, with the algorithms (typically Gibbs Sampler) implemented in the package JAGS ("Just Another Gibbs Sampler"). For convenience, the JAGS functions are called from R scripts, thus gaining the advantage given by the rich collection of mathematical, statistical and graphical functions included in the R installation. The results of the previous paper are thus easily re-obtained and the method is applied to the determination of the charged kaon mass. This note, based on lectures to PhD students and young researchers has been written with a didactic touch, and the relevant JAGS/rjags code is provided. (A curious bias arising from the sequential application of the $\sqrt{χ^2/ν}$ scaling prescription to 'apparently' discrepant results, found here, will be discussed in more detail in a separate paper.)
