Sheldon Wu:因果推理-Causal inference in statistics: a primer读书笔记-Chap2 Sheldon Wu:因果推理-Causal inference in statistics: a primer读书笔记-Chap3 Sheldon Wu:因果推理-Causal inference in statistics: a primer读书笔记-Chap4 Chap1:序言:统计和因果模型 -Preliminaries: Statistical and Causal Models 1...
Sheldon Wu:因果推理-Causal inference in statistics: a primer读书笔记-Chap4 Chap3:干预的神奇魔力 - The Effects of Interventions 通过干预,我们可以动态的控制一些本不该出现的,使我们迷惑的变量影响,更便捷的找到目标变量的之间的因果关系。 1. 干预(intervention)和固定(conditioning on)的区别 分两个方面来...
Causal Inference in Statistics, Social, and Biomedical Sciences豆瓣评分:8.9 简介:Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this g
Causal Inference in Statistics 作者:Judea Pearl 出版社:Wiley 副标题:A Primer 出版年:2016-2-19 页数:156 定价:GBP 27.99 装帧:Paperback ISBN:9781119186847 豆瓣评分 9.3 69人评价 5星 63.8% 4星 29.0% 3星 7.2% 2星 0.0% 1星 0.0% 评价:
3 (2009) 96–146ISSN: 1935-7516DOI: 10.1214/09-SS057Causal inference in statistics:An overview ∗†‡Judea PearlComputer Science DepartmentUniversity of California, Los Angeles, CA 90095 USAe-mail: judea@cs.ucla.eduAbstract: This reviewpresents empiricalresearcherswith recent advancesin causal...
1. Pearl, Judea, Madelyn Glymour, and Nicholas P. Jewell. Causal inference in statistics: A primer. John Wiley & Sons, 2016.(本书中译版《统计因果推理入门(翻译版)》已由高等教育出版社出版) 2. Peters, Jonas, Dominik Janzing, and Bernhard Schölkopf. Elements of causal inference: foundations...
Causal inference in statistics: An overview This review presents empirical researchers with recent advances in causal inference, and stresses the paradigmatic shifts that must be undertaken in moving... Pearl,Judea - 《Statistics Surveys》 被引量: 1029发表: 2009年 Causal inference in statistics. An...
在因果推理的世界里，反事实推理成为了一个强有力的工具。它通过假设某个条件的改变来预测结果，提供了一种对已发生事件的逆向思考方式。在统计学中，反事实推理不仅简化了对因果关系的理解，还为处理现实世界中的不确定性提供了方法。接下来，我们将探索反事实推理的精髓，包括其表示、基本准则、计算步骤、...
Causal Inference in Statistics fills that gap. Using simple examples and plain language, the book lays out how to define causal parameters; the assumptions necessary to estimate causal parameters in a variety of situations; how to express those assumptions mathematically; whether those assumptions have...