Strong Faithfulness and Uniform Consistency in Causal Inference

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Strong Faithfulness and Uniform Consistency in Causal Inference
A fundamental question in causal inference is whether it is possible to reliably infer the manipulation effects from observational data. There are a variety of senses of asymptotic reliability in the statistical literature, among which the most commonly discussed frequentist notions are pointwise consistency and uniform consistency (see, e.g. Bickel, Doksum [2001]). Uniform consistency is in general preferred to pointwise consistency because the former allows us to control the worst case error bounds with a finite sample size. In the sense of pointwise consistency, several reliable causal inference algorithms have been established under the Markov and Faithfulness assumptions [Pearl 2000, Spirtes et al. 2001]. In the sense of uniform consistency, however, reliable causal inference is impossible under the two assumptions when time order is unknown and/or latent confounders are present [Robins et al. 2000]. In this paper we present two natural generalizations of the Faithfulness assum...
Jiji Zhang, Peter Spirtes
Added 01 Nov 2010
Updated 01 Nov 2010
Type Conference
Year 2003
Where UAI
Authors Jiji Zhang, Peter Spirtes
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