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Causal Inference Using Graphical Models with the R Package pcalg

Citations

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Cited by:

  1. Epskamp, Sacha & Cramer, Angélique O.J. & Waldorp, Lourens J. & Schmittmann, Verena D. & Borsboom, Denny, 2012. "qgraph: Network Visualizations of Relationships in Psychometric Data," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i04).
  2. Aramayis Dallakyan, 2021. "Nonparanormal Structural VAR for Non-Gaussian Data," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1093-1113, April.
  3. Daniela Marella & Paola Vicard, 2022. "Bayesian network structural learning from complex survey data: a resampling based approach," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 981-1013, October.
  4. Timo Bettendorf & Reinhold Heinlein, 2023. "Connectedness between G10 currencies: Searching for the causal structure," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3938-3959, October.
  5. Aviral Kumar Tiwari & Micheal Kofi Boachie & Rangan Gupta, 2021. "Network Analysis of Economic and Financial Uncertainties in Advanced Economies: Evidence from Graph-Theory," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(1), pages 188-215, March.
  6. Rigana, Katerina & Wit, Ernst-Jan Camiel & Cook, Samantha, 2023. "A new way of measuring effects of financial crisis on contagion in currency markets," International Review of Financial Analysis, Elsevier, vol. 90(C).
  7. Katerina Rigana & Ernst C. Wit & Samantha Cook, 2024. "Navigating Market Turbulence: Insights from Causal Network Contagion Value at Risk," Papers 2402.06032, arXiv.org.
  8. Jinyang Zheng & Zhengling Qi & Yifan Dou & Yong Tan, 2019. "How Mega Is the Mega? Exploring the Spillover Effects of WeChat Using Graphical Model," Information Systems Research, INFORMS, vol. 30(4), pages 1343-1362, December.
  9. Daniela Marella, 2018. "Pc Complex: Pc Algorithm For Complex Survey Data," Departmental Working Papers of Economics - University 'Roma Tre' 0240, Department of Economics - University Roma Tre.
  10. Bettendorf, Timo & Heinlein, Reinhold, 2019. "Connectedness between G10 currencies: Searching for the causal structure," Discussion Papers 06/2019, Deutsche Bundesbank.
  11. Scutari, Marco, 2017. "Bayesian Network Constraint-Based Structure Learning Algorithms: Parallel and Optimized Implementations in the bnlearn R Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 77(i02).
  12. Ronja Foraita & Juliane Friemel & Kathrin Günther & Thomas Behrens & Jörn Bullerdiek & Rolf Nimzyk & Wolfgang Ahrens & Vanessa Didelez, 2020. "Causal discovery of gene regulation with incomplete data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1747-1775, October.
  13. Michimasa Fujiogi & Yoshihiko Raita & Marcos Pérez-Losada & Robert J. Freishtat & Juan C. Celedón & Jonathan M. Mansbach & Pedro A. Piedra & Zhaozhong Zhu & Carlos A. Camargo & Kohei Hasegawa, 2022. "Integrated relationship of nasopharyngeal airway host response and microbiome associates with bronchiolitis severity," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  14. Bouncken, Ricarda B. & Ratzmann, Martin & Kraus, Sascha, 2021. "Anti-aging: How innovation is shaped by firm age and mutual knowledge creation in an alliance," Journal of Business Research, Elsevier, vol. 137(C), pages 422-429.
  15. C. Wittenbecher & R. Cuadrat & L. Johnston & F. Eichelmann & S. Jäger & O. Kuxhaus & M. Prada & F. Del Greco M. & A. A. Hicks & P. Hoffman & J. Krumsiek & F. B. Hu & M. B. Schulze, 2022. "Dihydroceramide- and ceramide-profiling provides insights into human cardiometabolic disease etiology," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  16. Leonard Henckel & Emilija Perković & Marloes H. Maathuis, 2022. "Graphical criteria for efficient total effect estimation via adjustment in causal linear models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 579-599, April.
  17. Seán Roberts & James Winters, 2013. "Linguistic Diversity and Traffic Accidents: Lessons from Statistical Studies of Cultural Traits," PLOS ONE, Public Library of Science, vol. 8(8), pages 1-13, August.
  18. Daniela Scidá, 2023. "Structural VAR and financial networks: A minimum distance approach to spatial modeling," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(1), pages 49-68, January.
  19. Hobæk Haff, Ingrid & Aas, Kjersti & Frigessi, Arnoldo & Lacal, Virginia, 2016. "Structure learning in Bayesian Networks using regular vines," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 186-208.
  20. Rosa Aghdam & Mojtaba Ganjali & Parisa Niloofar & Changiz Eslahchi, 2016. "Inferring gene regulatory networks by an order independent algorithm using incomplete data sets," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 893-913, April.
  21. Peter Bühlmann, 2013. "Causal statistical inference in high dimensions," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 77(3), pages 357-370, June.
  22. Flaminia Musella & Paola Vicard & Maria Chiara De Angelis, 2022. "A Bayesian Network Model for Supporting School Managers Decisions in the Pandemic Era," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 163(3), pages 1445-1465, October.
  23. Aviral Kumar Tiwari & Micheal Kofi Boachie & Rangan Gupta, 2021. "Network Analysis of Economic and Financial Uncertainties in Advanced Economies: Evidence from Graph-Theory," Advances in Decision Sciences, Asia University, Taiwan, vol. 25(1), pages 188-215, March.
  24. Vincenzina Vitale & Flaminia Musella & Paola Vicard & Valentina Guizzi, 2020. "Modelling an energy market with Bayesian networks for non-normal data," Computational Management Science, Springer, vol. 17(1), pages 47-64, January.
  25. Jenny Häggström, 2018. "Rejoinder to Discussions on: Data†driven confounder selection via Markov and Bayesian networks," Biometrics, The International Biometric Society, vol. 74(2), pages 407-410, June.
  26. C Schultheiss & P Bühlmann, 2023. "Ancestor regression in linear structural equation models," Biometrika, Biometrika Trust, vol. 110(4), pages 1117-1124.
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