Efficient least squares for estimating total effects under linearity and causal sufficiency

8 August 2020

Papers citing "Efficient least squares for estimating total effects under linearity and causal sufficiency"

24 / 24 papers shown

Title
Minimal enumeration of all possible total effects in a Markov equivalence class F. R. Guo Emilija Perković CML 23 17 0 16 Oct 2020
Efficient adjustment sets in causal graphical models with hidden variables Ezequiel Smucler F. Sapienza A. Rotnitzky CML OffRL 50 32 0 22 Apr 2020
Estimating Treatment Effects with Observed Confounders and Mediators Shantanu Gupta Zachary Chase Lipton David Benjamin Childers CML 29 17 0 26 Mar 2020
On efficient adjustment in causal graphs Jan-Jelle Witte Leonard Henckel Marloes H. Maathuis Vanessa Didelez CML 52 69 0 17 Feb 2020
Efficient adjustment sets for population average treatment effect estimation in non-parametric causal graphical models A. Rotnitzky Ezequiel Smucler CML 58 30 0 01 Dec 2019
Center-Outward R-Estimation for Semiparametric VARMA Models Marc Hallin Davide La Vecchia Han Liu 74 37 0 18 Oct 2019
Identifying causal effects in maximally oriented partially directed acyclic graphs Emilija Perković CML 32 37 0 07 Oct 2019
Graphical Criteria for Efficient Total Effect Estimation via Adjustment in Causal Linear Models Leonard Henckel Emilija Perković Marloes H. Maathuis CML 62 104 0 04 Jul 2019
On Causal Discovery with Equal Variance Assumption Wenyu Chen Mathias Drton Y Samuel Wang CML 68 85 0 09 Jul 2018
Interpreting and using CPDAGs with background knowledge Emilija Perković M. Kalisch Marloes H. Maathuis 41 52 0 07 Jul 2017
Algebraic Problems in Structural Equation Modeling Mathias Drton 66 48 0 18 Dec 2016
Causal inference in partially linear structural equation models Dominik Rothenhausler J. Ernest M. Sugiyama 45 33 0 20 Jul 2016
Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs Emilija Perković J. Textor M. Kalisch Marloes H. Maathuis OffRL 59 144 0 22 Jun 2016
Structure Learning in Graphical Modeling Mathias Drton Marloes H. Maathuis CML 77 249 0 07 Jun 2016
A Complete Generalized Adjustment Criterion Emilija Perković J. Textor M. Kalisch Marloes H. Maathuis OffRL CML 41 72 0 06 Jul 2015
Causal Inference and Causal Explanation with Background Knowledge Christopher Meek CML 263 634 0 20 Feb 2013
Selection of Identifiability Criteria for Total Effects by using Path Diagrams Manabu Kuroki Zhihong Cai CML 76 38 0 11 Jul 2012
Causal discovery of linear acyclic models with arbitrary distributions P. Hoyer Aapo Hyvarinen R. Scheines Peter Spirtes Joseph Ramsey Gustavo Lacerda Shohei Shimizu CML 92 80 0 13 Jun 2012
Identifiability of Gaussian structural equation models with equal error variances J. Peters Peter Buhlmann CML 170 336 0 11 May 2012
On the Validity of Covariate Adjustment for Estimating Causal Effects I. Shpitser T. VanderWeele J. M. Robins CML 92 203 0 15 Mar 2012
Characterization and Greedy Learning of Interventional Markov Equivalence Classes of Directed Acyclic Graphs Alain Hauser Peter Buhlmann CML 90 424 0 14 Apr 2011
DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model Shohei Shimizu Takanori Inazumi Yasuhiro Sogawa Aapo Hyvarinen Yoshinobu Kawahara Takashi Washio P. Hoyer K. Bollen CML 102 510 0 13 Jan 2011
Global identifiability of linear structural equation models Mathias Drton Rina Foygel S. Sullivant 101 89 0 04 Mar 2010
Trek separation for Gaussian graphical models S. Sullivant Kelli Talaska J. Draisma 157 125 0 10 Dec 2008