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Practical Approaches to Causal Relationship ExplorationLocal Causal Discovery with a Simple PC Algorithm

Practical Approaches to Causal Relationship Exploration: Local Causal Discovery with a Simple PC... [This chapter presents the PC-simple algorithm and illustrates how to use the algorithm in the exploration for local causal relationships around a target variable. PC-simple is a simplified version of the PC algorithm, a classic method for learning a complete casual Bayesian network. We firstly discuss how the PC algorithm establishes causal relationships by the way of detecting persistent associations, then we introduce PC-simple in detail, followed by the discussions on PC-simple. The last section of this chapter introduces the R implementation of PC-simple.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Practical Approaches to Causal Relationship ExplorationLocal Causal Discovery with a Simple PC Algorithm

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Publisher
Springer International Publishing
Copyright
© The Author(s) 2015
ISBN
978-3-319-14432-0
Pages
9 –21
DOI
10.1007/978-3-319-14433-7_2
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter presents the PC-simple algorithm and illustrates how to use the algorithm in the exploration for local causal relationships around a target variable. PC-simple is a simplified version of the PC algorithm, a classic method for learning a complete casual Bayesian network. We firstly discuss how the PC algorithm establishes causal relationships by the way of detecting persistent associations, then we introduce PC-simple in detail, followed by the discussions on PC-simple. The last section of this chapter introduces the R implementation of PC-simple.]

Published: Mar 3, 2015

Keywords: Local Causal Discovery; Causal Bayesian Networks; Target Variable; Conditional Independence Tests; Causal DAGs

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