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Adjacency-Faithfulness and Conservative Causal Inference [article]

Joseph Ramsey, Jiji Zhang, Peter L. Spirtes
2012 arXiv   pre-print
Roughly the modified algorithm, called Conservative PC (CPC), checks whether Orientation-Faithfulness holds in the orientation phase, and if not, avoids drawing certain causal conclusions the PC algorithm  ...  Most causal inference algorithms in the literature (e.g., Pearl (2000), Spirtes et al. (2000), Heckerman et al. (1999)) exploit an assumption usually referred to as the causal Faithfulness or Stability  ...  -that we call CPC (conservative PC) -is correct given the Adjacency-Faithfulness condition, and is as informative as the standard PC algorithm if the Causal Faithfulness Condition actually obtains.  ... 
arXiv:1206.6843v1 fatcat:xa4jrgu7oneodaux3j2jr3ussy

Weakening faithfulness: some heuristic causal discovery algorithms

Zhalama, Jiji Zhang, Wolfgang Mayer
2016 International Journal of Data Science and Analytics  
In particular, we allow violations of Adjacency-Faithfulness and Orientation-Faithfulness.  ...  We examine the performance of some standard causal discovery algorithms, both constraint-based and score-based, from the perspective of how robust they are against (almost) failures of the causal Faithfulness  ...  In any case, it is probably safe to think that in most cases, PC is asymptotically correct in its inference of adjacencies (as opposed to its inference of non-adjacencies), even if Adjacency-Faithfulness  ... 
doi:10.1007/s41060-016-0033-y dblp:journals/ijdsa/ZhalamaZM17 fatcat:iy7dwguk5zbbnbz2m2bfbmi4yi

Detection of Unfaithfulness and Robust Causal Inference

Jiji Zhang, Peter Spirtes
2008 Minds and Machines  
Many algorithms proposed in the machine learning community for inferring causality from data are grounded on two assumptions, known as the Causal Markov Condition and the Causal Faithfulness Condition.  ...  The investigation yields a theoretical and a practical result: a strictly weaker Faithfulness condition which is nonetheless sufficient to justify some reliable methods of causal inference, and a way to  ...  It is in general true that only Adjacency-Faithfulness and Orientation-Faithfulness play a role in justifying causal inference procedures like PC.  ... 
doi:10.1007/s11023-008-9096-4 fatcat:qdb4zqkwebfr3bxocninod73ly

ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions [article]

Zhalama and Jiji Zhang and Frederick Eberhardt and Wolfgang Mayer and Mark Junjie Li
2019 arXiv   pre-print
In this paper, we study weakenings of Faithfulness for constraint-based discovery of semi-Markovian causal models, which accommodate the possibility of latent variables, and show that both (1) and (2)  ...  In recent years the possibility of relaxing the so-called Faithfulness assumption in automated causal discovery has been investigated.  ...  Given the causal Markov assumption, the Vadjacency-faithfulness assumption, V-adjacency-minimality assumption, and NoI-minimality assumptions are all conservative weakenings of the Faithfulness assumption  ... 
arXiv:1906.02385v1 fatcat:6d5h4yu4qnfdrh7l7lvg3bouea

A Bayesian Approach to Constraint Based Causal Inference [article]

Tom Claassen, Tom Heskes
2012 arXiv   pre-print
We target the problem of accuracy and robustness in causal inference from finite data sets.  ...  Tests show that a basic implementation of the resulting Bayesian Constraint-based Causal Discovery (BCCD) algorithm already outperforms established procedures such as FCI and Conservative PC.  ...  Again, see (Claassen and Heskes, 2012) for details. For example, identifying an absent causal relation (arrowhead) X ⇒ Y from an optimal uDAG becomes identical to the inference from a faithful MAG.  ... 
arXiv:1210.4866v1 fatcat:72jxpqxrnjclfjrp6totwt5bzu

SAT-Based Causal Discovery under Weaker Assumptions

Zhalama, Jiji Zhang, Frederick Eberhardt, Wolfgang Mayer
2017 Conference on Uncertainty in Artificial Intelligence  
Using the flexibility of recently developed methods for causal discovery based on Boolean satisfiability (SAT) solvers, we encode a variety of assumptions that weaken the Faithfulness assumption.  ...  This implementation of a whole set of assumptions in the same platform enables us to systematically explore the effect of weakening the Faithfulness assumption on causal discovery.  ...  Acknowledgements JZ's research was supported by the Research Grants Council of Hong Kong under the General Research Fund LU13600715 and by a Faculty Research Grant from Lingnan University.  ... 
dblp:conf/uai/ZhalamaZEM17 fatcat:bhhfpms465gazemg32zgmmprju

A Uniformly Consistent Estimator of Causal Effects under the $k$-Triangle-Faithfulness Assumption

Peter Spirtes, Jiji Zhang
2014 Statistical Science  
the Causal Markov assumption and the considerably weaker k-Triangle-Faithfulness assumption.  ...  by a directed acyclic graph for any parametric family with a uniformly consistent test of conditional independence, under the Causal Markov and Causal Faithfulness assumptions.  ...  First, S2 is the step of inferring adjacencies and non-adjacencies.  ... 
doi:10.1214/13-sts429 fatcat:yz5mc74smrgnffo22lfpzizy3m

Directed Conservative Causal Core Gene Networks [article]

Gokmen Altay
2018 bioRxiv   pre-print
Results: We modified a well-established conservative causal core network inference algorithm, C3NET, to be able to infer very large scale networks with direction information.  ...  We provide and R package and present performance results that are reproducible via the Supplementary file.  ...  Funding Research reported in this publication was supported by National Institute of Allergy and Infectious Diseases (NIAID) of the National Institutes of Health (NIH) under award number: R24AI108564.  ... 
doi:10.1101/271031 fatcat:jnfye5n5qfdmncmaga5bd5fo5y

Geometry of the faithfulness assumption in causal inference

Caroline Uhler, Garvesh Raskutti, Peter Bühlmann, Bin Yu
2013 Annals of Statistics  
Many algorithms for inferring causality rely heavily on the faithfulness assumption.  ...  We study the strong-faithfulness condition from a geometric and combinatorial point of view and give upper and lower bounds on the Lebesgue measure of strong-faithful distributions for various classes  ...  Most of the work by the first and second author was carried out while being at ETH Zürich and UC Berkeley, respectively.  ... 
doi:10.1214/12-aos1080 fatcat:2o54ywsujzdpfa3l2e4qpjb5ti

A Review on Algorithms for Constraint-based Causal Discovery [article]

Kui Yu, Jiuyong Li, Lin Liu
2016 arXiv   pre-print
Secondly and primarily, the state-of-the-art constraint-based casual inference algorithms are surveyed with the detailed analysis.  ...  diverse real-world problems due to the fast running speed and easy generalizing to the problem of causal insufficiency.  ...  [119] Assuming the causal Markov condition and the Adjacency-Faithfulness condition hold, any violation of the Orientation-Faithfulness condition is detectable. Very Conservative SGS Algorithm.  ... 
arXiv:1611.03977v2 fatcat:ercpfkqssnabfgdc3ndd7bd3tu

A Uniformly Consistent Estimator of non-Gaussian Causal Effects Under the k-Triangle-Faithfulness Assumption [article]

Shuyan Wang, Peter Spirtes
2021 arXiv   pre-print
Kalisch and Bühlmann (2007) showed that for linear Gaussian models, under the Causal Markov Assumption, the Strong Causal Faithfulness Assumption, and the assumption of causal sufficiency, the PC algorithm  ...  The k-Triangle-Faithfulness Assumption is a strictly weaker assumption that avoids some implausible implications of the Strong Causal Faithfulness Assumption and also allows for uniformly consistent estimates  ...  VCSGS Algorithm The algorithm we use to infer the structure of the underlying true causal graph is Very Conservative SGS (V CSGS) algorithm, which takes uniformly consistent tests of conditional independence  ... 
arXiv:2107.01333v2 fatcat:lkztmto35jhyrd3yx4zv6rnnka

The Frugal Inference of Causal Relations

Malcolm Forster, Garvesh Raskutti, Reuben Stern, Naftali Weinberger
2017 British Journal for the Philosophy of Science  
Zhang discusses three such razors: the causal Faithfulness condition, and two versions of the causal minimality condition.  ...  The CFC states that the true causal model is faithful to the true probability distribution.  ...  adjacency-faithfulness.  ... 
doi:10.1093/bjps/axw033 fatcat:mzkjr737obf3tg3kcoz7v2xv5y

Causal discovery for observational sciences using supervised machine learning [article]

Anne Helby Petersen, Joseph Ramsey, Claus Thorn Ekstrøm, Peter Spirtes
2022 arXiv   pre-print
This non-conservative error tradeoff is not ideal for observational sciences, where the resulting model is directly used to inform causal inference: A causal model with many missing causal relations entails  ...  Causal inference can estimate causal effects, but unless data are collected experimentally, statistical analyses must rely on pre-specified causal models.  ...  Acknowledgments: We thank Dan Saattrup Nielsen for guidance and help with the machine learning procedures. We thank Kun Zhang for his contributions to designing the project.  ... 
arXiv:2202.12813v2 fatcat:quh76y3gxjaulcjxe6ocb73fb4

Causal Inference Using Graphical Models with theRPackagepcalg

Markus Kalisch, Martin Mächler, Diego Colombo, Marloes H. Maathuis, Peter Bühlmann
2012 Journal of Statistical Software  
The pcalg package for R can be used for the following two purposes: Causal structure learning and estimation of causal effects from observational data.  ...  In this document, we give a brief overview of the methodology, and demonstrate the package's functionality in both toy examples and applications.  ...  We assume that the causal structure is unknown and want to infer the causal effect of V 2 on V 5 .  ... 
doi:10.18637/jss.v047.i11 fatcat:o3jxoq76yfdsdoe754nq26g62a

Conservative independence-based causal structure learning in absence of adjacency faithfulness

Jan Lemeire, Stijn Meganck, Francesco Cartella, Tingting Liu
2012 International Journal of Approximate Reasoning  
This paper presents an extension to the Conservative PC algorithm which is able to detect violations of adjacency faithfulness under causal sufficiency and triangle faithfulness.  ...  We prove that our Adjacency Conservative PC algorithm is able to correctly learn the f -pattern.  ...  We want to thank Alexander Statnikov, Angelos Armen and Sofia Triantafillou for their valuable comments.  ... 
doi:10.1016/j.ijar.2012.06.004 fatcat:oenou4bj4jfp3ivamsya6nlsyy
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