Prediction, Estimation, and Attribution
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Abstract
Suggested Citation
DOI: 10.1111/insr.12409
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Citations
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Cited by:
- Manski, Charles F., 2023.
"Probabilistic prediction for binary treatment choice: With focus on personalized medicine,"
Journal of Econometrics, Elsevier, vol. 234(2), pages 647-663.
- Charles F. Manski, 2021. "Probabilistic Prediction for Binary Treatment Choice: with Focus on Personalized Medicine," NBER Working Papers 29358, National Bureau of Economic Research, Inc.
- Charles F. Manski, 2021. "Probabilistic Prediction for Binary Treatment Choice: with focus on personalized medicine," Papers 2110.00864, arXiv.org.
- Ord, J. Keith, 2022. "The uncertainty track: Machine learning, statistical modeling, synthesis," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1526-1530.
- Jack Jewson & David Rossell, 2022. "General Bayesian loss function selection and the use of improper models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(5), pages 1640-1665, November.
- Nelson P. Rayl & Nitish R. Sinha, 2022. "Integrating Prediction and Attribution to Classify News," Finance and Economics Discussion Series 2022-042, Board of Governors of the Federal Reserve System (U.S.).
- Victor Quintas-Martinez & Mohammad Taha Bahadori & Eduardo Santiago & Jeff Mu & Dominik Janzing & David Heckerman, 2024. "Multiply-Robust Causal Change Attribution," Papers 2404.08839, arXiv.org.
- COJOCARIU Irina-Cristina, 2023. "Analysis Of Sports Performances Using Machine Learning And Statistical Models - A General Analysis Of The Literature," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 75(2), pages 34-39, June.
- Benítez-Peña, Sandra & Carrizosa, Emilio & Guerrero, Vanesa & Jiménez-Gamero, M. Dolores & Martín-Barragán, Belén & Molero-Río, Cristina & Ramírez-Cobo, Pepa & Romero Morales, Dolores & Sillero-Denami, 2021. "On sparse ensemble methods: An application to short-term predictions of the evolution of COVID-19," European Journal of Operational Research, Elsevier, vol. 295(2), pages 648-663.
- Rich, Jeppe & Myhrmann, Marcus Skyum & Mabit, Stefan Eriksen, 2023. "Our children cycle less - A Danish pseudo-panel analysis," Journal of Transport Geography, Elsevier, vol. 106(C).
- M. Merz & R. Richman & T. Tsanakas & M. V. Wuthrich, 2021. "Interpreting Deep Learning Models with Marginal Attribution by Conditioning on Quantiles," Papers 2103.11706, arXiv.org.
- Chun Chieh Fan & Robert Loughnan & Carolina Makowski & Diliana Pecheva & Chi-Hua Chen & Donald J. Hagler & Wesley K. Thompson & Nadine Parker & Dennis van der Meer & Oleksandr Frei & Ole A. Andreassen, 2022. "Multivariate genome-wide association study on tissue-sensitive diffusion metrics highlights pathways that shape the human brain," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
- Anna Gottard & Giulia Vannucci & Leonardo Grilli & Carla Rampichini, 2023. "Mixed-effect models with trees," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 17(2), pages 431-461, June.
- Denis A Shah & Erick D De Wolf & Pierce A Paul & Laurence V Madden, 2021. "Accuracy in the prediction of disease epidemics when ensembling simple but highly correlated models," PLOS Computational Biology, Public Library of Science, vol. 17(3), pages 1-23, March.
- Jeff Dominitz & Charles F. Manski, 2024. "Comprehensive OOS Evaluation of Predictive Algorithms with Statistical Decision Theory," Papers 2403.11016, arXiv.org.
- Weishampel, Anthony & Staicu, Ana-Maria & Rand, William, 2023. "Classification of social media users with generalized functional data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
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