Random forests for global sensitivity analysis: A selective review
Author
Abstract
Suggested Citation
DOI: 10.1016/j.ress.2020.107312
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Wei, Pengfei & Lu, Zhenzhou & Song, Jingwen, 2015. "Variable importance analysis: A comprehensive review," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 399-432.
- Gregorutti, Baptiste & Michel, Bertrand & Saint-Pierre, Philippe, 2015. "Grouped variable importance with random forests and application to multiple functional data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 90(C), pages 15-35.
- Stefan Wager & Susan Athey, 2018.
"Estimation and Inference of Heterogeneous Treatment Effects using Random Forests,"
Journal of the American Statistical Association, Taylor & Francis Journals, vol. 113(523), pages 1228-1242, July.
- Wager, Stefan & Athey, Susan, 2017. "Estimation and Inference of Heterogeneous Treatment Effects Using Random Forests," Research Papers 3576, Stanford University, Graduate School of Business.
- Stan Lipovetsky & Michael Conklin, 2001. "Analysis of regression in game theory approach," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 17(4), pages 319-330, October.
- Richard Bellman, 1957. "On a Dynamic Programming Approach to the Caterer Problem--I," Management Science, INFORMS, vol. 3(3), pages 270-278, April.
- Sudret, Bruno, 2008. "Global sensitivity analysis using polynomial chaos expansions," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 964-979.
- Matthew Gentzkow & Bryan Kelly & Matt Taddy, 2019. "Text as Data," Journal of Economic Literature, American Economic Association, vol. 57(3), pages 535-574, September.
- Gérard Biau & Erwan Scornet, 2016. "A random forest guided tour," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 197-227, June.
- Manel Baucells & Emanuele Borgonovo, 2013. "Invariant Probabilistic Sensitivity Analysis," Management Science, INFORMS, vol. 59(11), pages 2536-2549, November.
- Constantine, Paul G. & Diaz, Paul, 2017. "Global sensitivity metrics from active subspaces," Reliability Engineering and System Safety, Elsevier, vol. 162(C), pages 1-13.
- Liu, Qiao & Homma, Toshimitsu, 2009. "A new computational method of a moment-independent uncertainty importance measure," Reliability Engineering and System Safety, Elsevier, vol. 94(7), pages 1205-1211.
- Gérard Biau & Erwan Scornet, 2016. "Rejoinder on: A random forest guided tour," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(2), pages 264-268, June.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Borup, Daniel & Christensen, Bent Jesper & Mühlbach, Nicolaj Søndergaard & Nielsen, Mikkel Slot, 2023.
"Targeting predictors in random forest regression,"
International Journal of Forecasting, Elsevier, vol. 39(2), pages 841-868.
- Daniel Borup & Bent Jesper Christensen & Nicolaj N. Mühlbach & Mikkel S. Nielsen, 2020. "Targeting predictors in random forest regression," CREATES Research Papers 2020-03, Department of Economics and Business Economics, Aarhus University.
- Daniel Borup & Bent Jesper Christensen & Nicolaj N{o}rgaard Muhlbach & Mikkel Slot Nielsen, 2020. "Targeting predictors in random forest regression," Papers 2004.01411, arXiv.org, revised Nov 2020.
- Patrick Krennmair & Timo Schmid, 2022. "Flexible domain prediction using mixed effects random forests," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(5), pages 1865-1894, November.
- Escribano, Álvaro & Wang, Dandan, 2021. "Mixed random forest, cointegration, and forecasting gasoline prices," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1442-1462.
- Yigit Aydede & Jan Ditzen, 2022. "Identifying the regional drivers of influenza-like illness in Nova Scotia with dominance analysis," Papers 2212.06684, arXiv.org.
- Daniel Boller & Michael Lechner & Gabriel Okasa, 2025.
"The effect of sport in online dating: evidence from causal machine learning,"
Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-13, December.
- Boller, Daniel & Lechner, Michael & Okasa, Gabriel, 2021. "The Effect of Sport in Online Dating: Evidence from Causal Machine Learning," Economics Working Paper Series 2104, University of St. Gallen, School of Economics and Political Science.
- Boller, Daniel & Lechner, Michael & Okasa, Gabriel, 2021. "The Effect of Sport in Online Dating: Evidence from Causal Machine Learning," IZA Discussion Papers 14259, Institute of Labor Economics (IZA).
- Daniel Boller & Michael Lechner & Gabriel Okasa, 2021. "The Effect of Sport in Online Dating: Evidence from Causal Machine Learning," Papers 2104.04601, arXiv.org.
- Susan Athey & Julie Tibshirani & Stefan Wager, 2016.
"Generalized Random Forests,"
Papers
1610.01271, arXiv.org, revised Apr 2018.
- Athey, Susan & Tibshirani, Julie & Wager, Stefan, 2017. "Generalized Random Forests," Research Papers 3575, Stanford University, Graduate School of Business.
- Marrel, Amandine & Chabridon, Vincent, 2021. "Statistical developments for target and conditional sensitivity analysis: Application on safety studies for nuclear reactor," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
- Michael Lechner & Gabriel Okasa, 2025.
"Random Forest estimation of the ordered choice model,"
Empirical Economics, Springer, vol. 68(1), pages 1-106, January.
- Michael Lechner & Gabriel Okasa, 2019. "Random Forest Estimation of the Ordered Choice Model," Papers 1907.02436, arXiv.org, revised Sep 2022.
- Lechner, Michael & Okasa, Gabriel, 2019. "Random Forest Estimation of the Ordered Choice Model," Economics Working Paper Series 1908, University of St. Gallen, School of Economics and Political Science.
- Kayo Murakami & Hideki Shimada & Yoshiaki Ushifusa & Takanori Ida, 2022.
"Heterogeneous Treatment Effects Of Nudge And Rebate: Causal Machine Learning In A Field Experiment On Electricity Conservation,"
International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(4), pages 1779-1803, November.
- Kayo MURAKAMI & Hideki SHIMADA & Yoshiaki USHIFUSA & Takanori IDA, 2020. "Heterogeneous Treatment Effects of Nudge and Rebate:Causal Machine Learning in a Field Experiment on Electricity Conservation," Discussion papers e-20-003, Graduate School of Economics , Kyoto University.
- Emilio Carrizosa & Cristina Molero-Río & Dolores Romero Morales, 2021. "Mathematical optimization in classification and regression trees," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(1), pages 5-33, April.
- Schnaubelt, Matthias & Fischer, Thomas G. & Krauss, Christopher, 2020. "Separating the signal from the noise – Financial machine learning for Twitter," Journal of Economic Dynamics and Control, Elsevier, vol. 114(C).
- Daniel Goller & Michael C. Knaus & Michael Lechner & Gabriel Okasa, 2021.
"Predicting match outcomes in football by an Ordered Forest estimator,"
Chapters, in: Ruud H. Koning & Stefan Kesenne (ed.), A Modern Guide to Sports Economics, chapter 22, pages 335-355,
Edward Elgar Publishing.
- Goller, Daniel & Knaus, Michael C. & Lechner, Michael & Okasa, Gabriel, 2018. "Predicting Match Outcomes in Football by an Ordered Forest Estimator," Economics Working Paper Series 1811, University of St. Gallen, School of Economics and Political Science.
- Tatsuya Sakurahara & Seyed Reihani & Ernie Kee & Zahra Mohaghegh, 2020. "Global importance measure methodology for integrated probabilistic risk assessment," Journal of Risk and Reliability, , vol. 234(2), pages 377-396, April.
- Gabriel Okasa, 2022. "Meta-Learners for Estimation of Causal Effects: Finite Sample Cross-Fit Performance," Papers 2201.12692, arXiv.org.
- Yiyi Huo & Yingying Fan & Fang Han, 2023. "On the adaptation of causal forests to manifold data," Papers 2311.16486, arXiv.org, revised Dec 2023.
- Max Biggs & Rim Hariss & Georgia Perakis, 2023. "Constrained optimization of objective functions determined from random forests," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 397-415, February.
- Valente, Marica, 2023.
"Policy evaluation of waste pricing programs using heterogeneous causal effect estimation,"
Journal of Environmental Economics and Management, Elsevier, vol. 117(C).
- Marica Valente, 2020. "Policy evaluation of waste pricing programs using heterogeneous causal effect estimation," Papers 2010.01105, arXiv.org, revised Nov 2022.
- Marica Valente, 2021. "Policy Evaluation of Waste Pricing Programs Using Heterogeneous Causal Effect Estimation," Discussion Papers of DIW Berlin 1980, DIW Berlin, German Institute for Economic Research.
- Pedro Forquesato, 2022. "Who Benefits from Political Connections in Brazilian Municipalities," Papers 2204.09450, arXiv.org.
- Ruixin Liang & Joanne Yip & Yunli Fan & Jason P. Y. Cheung & Kai-Tsun Michael To, 2022. "Electromyographic Analysis of Paraspinal Muscles of Scoliosis Patients Using Machine Learning Approaches," IJERPH, MDPI, vol. 19(3), pages 1-12, January.
- Nathan Kallus & Xiaojie Mao, 2023. "Stochastic Optimization Forests," Management Science, INFORMS, vol. 69(4), pages 1975-1994, April.
More about this item
Keywords
Random forests; Global sensitivity analysis;Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:reensy:v:206:y:2021:i:c:s0951832020308073. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.