Quantifying causal influences
نویسندگان
چکیده
منابع مشابه
Quantifying Causal Influences
Many methods for causal inference generate directed acyclic graphs (DAGs) that formalize causal relations between n variables. Given the joint distribution on all these variables, the DAG contains all information about how intervening on one variable changes the distribution of the other n− 1 variables. However, quantifying the causal influence of one variable on another one remains a nontrivia...
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Recent data mining techniques exploit patterns of statistical independence in multivariate data to make conjectures about cause/effect relationships. These relationships can be used to construct causal graphs, which are sometimes represented by weighted node-link diagrams, with nodes representing variables and combinations of weighted links and/or nodes showing the strength of causal relationsh...
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Causal interactions within complex systems can be analyzed at multiple spatial and temporal scales. For example, the brain can be analyzed at the level of neurons, neuronal groups, and areas, over tens, hundreds, or thousands of milliseconds. It is widely assumed that, once a micro level is fixed, macro levels are fixed too, a relation called supervenience. It is also assumed that, although mac...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2013
ISSN: 0090-5364
DOI: 10.1214/13-aos1145