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Consistency of Causal Inference under the Additive Noise Model

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arxiv 1312.5770 v3 pith:RUUI6Q3O submitted 2013-12-19 cs.LG stat.ML

Consistency of Causal Inference under the Additive Noise Model

classification cs.LG stat.ML
keywords inferenceadditivecausalmethodsmodelnoiseunderconsistency
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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We analyze a family of methods for statistical causal inference from sample under the so-called Additive Noise Model. While most work on the subject has concentrated on establishing the soundness of the Additive Noise Model, the statistical consistency of the resulting inference methods has received little attention. We derive general conditions under which the given family of inference methods consistently infers the causal direction in a nonparametric setting.

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