Scholarlink

Causal graphs offer a powerful and intuitive way to represent assumptions about cause-and-effect relationships among variables. They use directed edges to encode causal relationships and provide a visual framework for reasoning about the flow of causality, detecting biases, and designing strategies for causal estimation.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Causal Graphs: Structure and Assumptions

  • 章节

  • 发表日期：

    2025年

查看全文
  • Durai Rajamanickam

摘要

Causal graphs offer a powerful and intuitive way to represent assumptions about cause-and-effect relationships among variables. They use directed edges to encode causal relationships and provide a visual framework for reasoning about the flow of causality, detecting biases, and designing strategies for causal estimation.