线性结构方程模型中的反事实推理

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摘要翻译：
考虑变量之间的因果关系可以描述为高斯线性结构方程模型的情况。本文讨论了如果一个治疗变量被赋予某个值（反事实），如果一组变量被观察到（实际上），一个反应变量的方差将如何改变的问题。为了达到这一目的，我们通过观测变量的总效应和协方差矩阵重新表述了Balke和Pearl(1995)提出的反事实分布公式。我们进一步将Balke和Pearl(1995)的框架从点观测推广到区间观测，从无条件计划推广到条件计划。本文的结果使我们能够澄清反事实分布的性质，并建立最优方案。
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英文标题：
《Counterfactual Reasoning in Linear Structural Equation Models》
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作者：
Zhihong Cai, Manabu Kuroki
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最新提交年份：
2012
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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英文摘要：
  Consider the case where causal relations among variables can be described as a Gaussian linear structural equation model. This paper deals with the problem of clarifying how the variance of a response variable would have changed if a treatment variable were assigned to some value (counterfactually), given that a set of variables is observed (actually). In order to achieve this aim, we reformulate the formulas of the counterfactual distribution proposed by Balke and Pearl (1995) through both the total effects and a covariance matrix of observed variables. We further extend the framework of Balke and Pearl (1995) from point observations to interval observations, and from an unconditional plan to a conditional plan. The results of this paper enable us to clarify the properties of counterfactual distribution and establish an optimal plan.
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PDF链接：
https://arxiv.org/pdf/1207.1376

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关键词：结构方程模型 结构方程 distribution observations Intelligence 事实 variable 推广 达到 观测