Keyword

PC algorithm

Description: A constraint-based algorithm for learning the structure of directed acyclic graphs from observational data, commonly used to infer causal relationships.

Primary topic: Bayesian Modeling and Causal Inference (66%)

Wikidata ID: wiki/Q123578022

OpenAlex ID: keywords/pc-algorithm

The max-min hill-climbing Bayesian network structure learning algorithm

2006 · Ioannis Tsamardinos, Laura E. Brown, et al. · Machine Learning · 1,824

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Estimating high-dimensional directed acyclic graphs with the PC-algorithm

2005 · Kalisch, Markus, Buehlmann, Peter · arXiv (Cornell University) · 704

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Order-independent constraint-based causal structure learning

2014 · Diego Colombo, Marloes H. Maathuis · arXiv (Cornell University) · 454

Escaping the Curse of Dimensionality in Estimating Multivariate Transfer Entropy

2012 · Jakob Runge, Jobst Heitzig, et al. · Physical Review Letters · 346

Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm

2007 · KalischMarkus, BühlmannPeter · Journal of Machine Learning Research · 330

Searching for the Causal Structure of a Vector Autoregression*

2003 · Selva Demiralp, Kevin D. Hoover · Oxford Bulletin of Economics and Statistics · 228

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Structure Learning in Graphical Modeling

2016 · Mathias Drton, Marloes H. Maathuis · Annual Review of Statistics and Its Application · 210

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Using Markov Blankets for Causal Structure Learning

2008 · Jean‐Philippe Pellet, André Elisseeff · Journal of Machine Learning Research · 196

A Study of Contemporaneous Residential Real Estate Price Causation Across Major Jiangsu Province Cities: Methodology Using Vector Error-Correction Models and Directed Acyclic Graphs

2025 · Bingzi Jin, Xiaojie Xu · Economics Open · 181

Contemporaneous causal orderings among prices of retail properties: evidence from Chinese cities through vector error-correction modeling and directed acyclic graphs

2025 · Bingzi Jin, Xiaojie Xu · Journal of Financial Management of Property and Construction · 180

Adjacency-Faithfulness and Conservative Causal Inference

2012 · Ramsey, Joseph, Zhang, Jiji, et al. · arXiv (Cornell University) · 170

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Geometry of the faithfulness assumption in causal inference

2013 · Caroline Uhler, Garvesh Raskutti, et al. · The Annals of Statistics · 149

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A Fast PC Algorithm for High Dimensional Causal Discovery with Multi-Core PCs

2016 · Thuc Duy Le, Tao Hoang, et al. · IEEE Transactions on Computational Biology and Bioinformatics · 136

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Bayesian network learning algorithms using structural restrictions

2006 · Luis M. de Campos, Javier G. Castellano · International Journal of Approximate Reasoning · 120

Variable selection in high-dimensional linear models: partially faithful distributions and the PC-simple algorithm

2010 · P. Buhlmann, M. Kalisch, et al. · Biometrika · 115

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PC algorithm for nonparanormal graphical models

2013 · Naftali Harris, Mathias Drton · mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) · 106

Contemporaneous causal orderings of US corn cash prices through directed acyclic graphs

2016 · Xiaojie Xu · Empirical Economics · 105

Discovering contemporaneous and lagged causal relations in autocorrelated nonlinear time series datasets

2020 · Runge, Jakob · arXiv (Cornell University) · 104

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High-dimensional consistency in score-based and hybrid structure learning

2018 · Preetam Nandy, Alain Hauser, et al. · The Annals of Statistics · 100

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A parallel algorithm for Bayesian network structure learning from large data sets

2016 · Anders L. Madsen, Frank Jensen, et al. · Knowledge-Based Systems · 82

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Are There Algorithms That Discover Causal Structure?