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  • Search: subject:"Super learning"
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Year of publication
Subject
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super learning 2 Cross validation 1 Functional linear model 1 Model stacking 1 Super learning 1 atrial fibrillation 1 bisphosphonate therapy 1 causal inference 1 comparative effectiveness and safety 1 data reduction 1 doubly robust 1 inverse probability weighting estimation 1 macroeconomics 1 marginal structural model 1 monetary policy 1
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Online availability
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Free 2 CC license 1 Undetermined 1
Type of publication
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Article 3
Type of publication (narrower categories)
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research-article 2
Language
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English 2 Undetermined 1
Author
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Baumann, Philipp F. M. 1 Chandra, Malini 1 Goldsmith, Jeff 1 J. Graham, David 1 McCloskey, Carolyn 1 Neugebauer, Romain 1 Paredes, Antonio 1 Rossi, Enzo 1 S. Go, Alan 1 Scheipl, Fabian 1 Schomaker, Michael 1
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Published in...
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Journal of Causal Inference 2 Computational Statistics & Data Analysis 1
Source
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Other ZBW resources 2 RePEc 1
Showing 1 - 3 of 3
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Estimating the effect of central bank independence on inflation using longitudinal targeted maximum likelihood estimation
Baumann, Philipp F. M.; Schomaker, Michael; Rossi, Enzo - In: Journal of Causal Inference 9 (2021) 1, pp. 109-146
Abstract The notion that an independent central bank reduces a country’s inflation is a controversial hypothesis. To date, it has not been possible to satisfactorily answer this question because the complex macroeconomic structure that gives rise to the data has not been adequately...
Persistent link: https://www.econbiz.de/10014610904
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A Marginal Structural Modeling Approach with Super Learning for a Study on Oral Bisphosphonate Therapy and Atrial Fibrillation
Neugebauer, Romain; Chandra, Malini; Paredes, Antonio; … - In: Journal of Causal Inference 1 (2013) 1, pp. 21-50
data reduction and super learning. Methods : We describe the principles of, motivation for, and implementation of an … in the application of the current R implementation of super learning with large data sets. While computing time and … memory requirements did not permit aggressive estimator selection with super learning, this analysis demonstrates the …
Persistent link: https://www.econbiz.de/10014610784
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Estimator selection and combination in scalar-on-function regression
Goldsmith, Jeff; Scheipl, Fabian - In: Computational Statistics & Data Analysis 70 (2014) C, pp. 362-372
Scalar-on-function regression problems with continuous outcomes arise naturally in many settings, and a wealth of estimation methods now exist. Despite the clear differences in regression model assumptions, tuning parameter selection, and the incorporation of functional structure, it remains...
Persistent link: https://www.econbiz.de/10010719696
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