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Penyesuaian Pintu Depan (Kriteria Pintu Depan)×Algoritma Penemuan Kausal (PC, FCI, LiNGAM)×
BidangInferensi KausalInferensi Kausal
KeluargaRegression modelRegression model
Tahun asal19952000
PencetusJudea PearlSpirtes, Glymour & Scheines (PC/FCI); Shimizu et al. (LiNGAM)
TipeCausal identification (graphical adjustment)Causal structure learning
Sumber perintisPearl, J. (1995). Causal Diagrams for Empirical Research. Biometrika, 82(4), 669-688. DOI ↗Spirtes, P., Glymour, C., & Scheines, R. (2000). Causation, Prediction, and Search (2nd ed.). MIT Press. ISBN: 978-0262194402
Aliasfrontdoor criterion, Pearl's frontdoor adjustment, frontdoor formula, Ön Kapı Düzenlemesi (Frontdoor Adjustment)PC algorithm, FCI algorithm, LiNGAM, causal structure learning
Terkait45
RingkasanFrontdoor adjustment is Judea Pearl's graphical identification strategy, introduced in 1995, that recovers the causal effect of a treatment on an outcome through a fully mediating variable even when an unobserved confounder sits between the treatment and the outcome. It is the go-to tool when the backdoor criterion cannot be satisfied because the confounder is unmeasured.Causal discovery is a family of algorithms that automatically learn a directed acyclic graph (DAG) describing causal structure directly from observational data. The constraint-based PC and FCI algorithms were developed by Spirtes, Glymour and Scheines (2000), while the LiNGAM model of Shimizu et al. (2006) exploits linear non-Gaussian structure to orient edges.
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ScholarGateBandingkan metode: Frontdoor Adjustment · Causal Discovery Algorithms. Diakses 2026-06-18 dari https://scholargate.app/id/compare