IDEAS home Printed from https://ideas.repec.org/r/mtp/titles/0262194406.html

Causation, Prediction, and Search, 2nd Edition

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Chen, Pu & Hsiao, Chih-Ying, 2008. "What happens to Japan if China catches a cold?: A causal analysis of Chinese growth and Japanese growth," Japan and the World Economy, Elsevier, vol. 20(4), pages 622-638, December.
  2. Stimel Derek S, 2011. "Dependence Relationships between On Field Performance, Wins, and Payroll in Major League Baseball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(2), pages 1-19, May.
  3. Ziyang Jiao & Ce Guo & Wayne Luk, 2025. "Scalable Time Series Causal Discovery with Approximate Causal Ordering," Mathematics, MDPI, vol. 13(20), pages 1-15, October.
  4. Tyler J. VanderWeele, 2011. "Sensitivity Analysis for Contagion Effects in Social Networks," Sociological Methods & Research, , vol. 40(2), pages 240-255, May.
  5. Bareinboim Elias & Pearl Judea, 2013. "A General Algorithm for Deciding Transportability of Experimental Results," Journal of Causal Inference, De Gruyter, vol. 1(1), pages 107-134, June.
  6. Benjamin A Logsdon & Jason Mezey, 2010. "Gene Expression Network Reconstruction by Convex Feature Selection when Incorporating Genetic Perturbations," PLOS Computational Biology, Public Library of Science, vol. 6(12), pages 1-13, December.
  7. Zhang, Qi & Wang, Weihua & She, Jiani & Ma, Zhenliang, 2025. "Understanding bus network delay propagation: Integration of causal inference and complex network theory," Journal of Transport Geography, Elsevier, vol. 123(C).
  8. Ahn, Youngmin & Park, Woongjoon & Park, Gunwoong, 2025. "Discretization: Privacy-preserving data publishing for causal discovery," Computational Statistics & Data Analysis, Elsevier, vol. 209(C).
  9. Stimel Derek, 2009. "A Statistical Analysis of NFL Quarterback Rating Variables," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 5(2), pages 1-26, May.
  10. Huang, Wei & Lai, Pei-Chun & Bessler, David A., 2018. "On the changing structure among Chinese equity markets: Hong Kong, Shanghai, and Shenzhen," European Journal of Operational Research, Elsevier, vol. 264(3), pages 1020-1032.
  11. Bettendorf, Timo & Heinlein, Reinhold, 2019. "Connectedness between G10 currencies: Searching for the causal structure," Discussion Papers 06/2019, Deutsche Bundesbank.
  12. Kaiyue Liu & Lihua Liu & Kaiming Xiao & Xuan Li & Hang Zhang & Yun Zhou & Hongbin Huang, 2024. "CL-NOTEARS: Continuous Optimization Algorithm Based on Curriculum Learning Framework," Mathematics, MDPI, vol. 12(17), pages 1-22, August.
  13. Maarten J. Bijlsma & Rhian Daniel & Fanny Janssen & Bianca De Stavola, 2016. "An assessment and extension of the mechanism-based approach to the identification of age-period-cohort models," MPIDR Working Papers WP-2016-005, Max Planck Institute for Demographic Research, Rostock, Germany.
  14. Xingyu Liao & Xiaoping Liu, 2024. "Hidden Variable Discovery Based on Regression and Entropy," Mathematics, MDPI, vol. 12(9), pages 1-16, April.
  15. Leonelli, Manuele & Varando, Gherardo, 2024. "Robust learning of staged tree models: A case study in evaluating transport services," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
  16. Dong, Pingping & Zhang, Xiaoning & Zhang, Xiaoge, 2025. "A data-driven approach for spatio-temporal causal analysis in large-scale urban traffic networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 202(C).
  17. Steven Sheffrin & Rujun Zhao, 2021. "Public perceptions of the tax avoidance of corporations and the wealthy," Empirical Economics, Springer, vol. 61(1), pages 259-277, July.
  18. Chen, Pu & Chihying, Hsiao, 2007. "Learning Causal Relations in Multivariate Time Series Data," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy, vol. 1, pages 1-43.
  19. Klimova, Anna & Uhler, Caroline & Rudas, Tamás, 2015. "Faithfulness and learning hypergraphs from discrete distributions," Computational Statistics & Data Analysis, Elsevier, vol. 87(C), pages 57-72.
  20. Hao Li & Jianjun Zhan & Haosen Wang & Zipeng Zhao, 2024. "A Novel Ensemble Method of Divide-and-Conquer Markov Boundary Discovery for Causal Feature Selection," Mathematics, MDPI, vol. 12(18), pages 1-21, September.
  21. Maarten J. Bijlsma & Rhian M. Daniel & Fanny Janssen & Bianca L. De Stavola, 2017. "An Assessment and Extension of the Mechanism-Based Approach to the Identification of Age-Period-Cohort Models," Demography, Springer;Population Association of America (PAA), vol. 54(2), pages 721-743, April.
  22. David Atienza & Pedro Larrañaga & Concha Bielza, 2022. "Hybrid semiparametric Bayesian networks," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 31(2), pages 299-327, June.
  23. Liu, Tianyu & Mukherjee, Somabha & Biswas, Rahul, 2024. "Tensor recovery in high-dimensional Ising models," Journal of Multivariate Analysis, Elsevier, vol. 203(C).
  24. Paul Muentener & Elizabeth Bonawitz & Alexandra Horowitz & Laura Schulz, 2012. "Mind the Gap: Investigating Toddlers’ Sensitivity to Contact Relations in Predictive Events," PLOS ONE, Public Library of Science, vol. 7(4), pages 1-7, April.
  25. Selva Demiralp & Kevin Hoover & Stephen Perez, 2014. "Still puzzling: evaluating the price puzzle in an empirically identified structural vector autoregression," Empirical Economics, Springer, vol. 46(2), pages 701-731, March.
  26. Álvaro Martínez-Sánchez & Gonzalo Arranz & Adrián Lozano-Durán, 2024. "Decomposing causality into its synergistic, unique, and redundant components," Nature Communications, Nature, vol. 15(1), pages 1-15, December.
  27. Ruijie Tang, 2024. "Trading with Time Series Causal Discovery: An Empirical Study," Papers 2408.15846, arXiv.org, revised Aug 2024.
  28. Papanicolaou, Athanasios (Thanos) N. & Basnet, Keshav & O’Brien, Peter L. & Wacha, Kenneth M. & Malone, Robert W. & Archer, David W., 2025. "A system dynamics modeling framework to evaluate impacts on economic, environmental, and social quality components of a U.S. Midwestern agroecosystem transitioning from row crop agriculture to mixed farming systems," Ecological Modelling, Elsevier, vol. 506(C).
  29. Jong-Min Kim & Chulhee Jun & Hope H. Han, 2020. "Sustainable Causal Interpretation with Board Characteristics: Caveat Emptor," Sustainability, MDPI, vol. 12(8), pages 1-18, April.
  30. Pearl Judea, 2017. "Physical and Metaphysical Counterfactuals: Evaluating Disjunctive Actions," Journal of Causal Inference, De Gruyter, vol. 5(2), pages 1-10, September.
  31. Yi Jiang & Shohei Shimizu, 2024. "Does Financial Literacy Impact Investment Participation and Retirement Planning in Japan?," Papers 2405.01078, arXiv.org.
  32. Heinlein, Reinhold & Krolzig, Hans-Martin, 2012. "On the construction of two-country cointegrated VAR models with an application to the UK and US," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62310, Verein für Socialpolitik / German Economic Association.
  33. Behnam Azhdari & Jean Bonnet & Sébastien Bourdin, 2022. "Towards a Causal Model and Causal Inference of Regional Entrepreneurship Development Index, its antecedents and outcomes in European regions," Economics Working Paper Archive (University of Rennes & University of Caen) 2022-06, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
  34. Heckman, James & Pinto, Rodrigo, 2024. "Econometric causality: The central role of thought experiments," Journal of Econometrics, Elsevier, vol. 243(1).
  35. C Schultheiss & P Bühlmann, 2023. "Ancestor regression in linear structural equation models," Biometrika, Biometrika Trust, vol. 110(4), pages 1117-1124.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.