English

Fast Restricted Causal Inference

Artificial Intelligence 2017-07-18 v1

Abstract

Hidden variables are well known sources of disturbance when recovering belief networks from data based only on measurable variables. Hence models assuming existence of hidden variables are under development. This paper presents a new algorithm "accelerating" the known CI algorithm of Spirtes, Glymour and Scheines {Spirtes:93}. We prove that this algorithm does not produces (conditional) independencies not present in the data if statistical independence test is reliable. This result is to be considered as non-trivial since e.g. the same claim fails to be true for FCI algorithm, another "accelerator" of CI, developed in {Spirtes:93}.

Cite

@article{arxiv.1707.04584,
  title  = {Fast Restricted Causal Inference},
  author = {Mieczysław A. Kłopotek},
  journal= {arXiv preprint arXiv:1707.04584},
  year   = {2017}
}

Comments

1995 internal report. arXiv admin note: substantial text overlap with arXiv:1705.10308, arXiv:1706.10117; text overlap with arXiv:1707.03881

R2 v1 2026-06-22T20:47:27.898Z