SuperLearner

R package SuperLearner: Super Learner Prediction. This package implements the super learner prediction method and contains a library of prediction algorithms to be used in the super learner.

Keywords for this software

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References in zbMATH (referenced in 19 articles )

Showing results 1 to 19 of 19.
Sorted by year (citations)

  1. Boehmke, Brad; Greenwell, Brandon M.: Hands-on machine learning with R (2020)
  2. Chi Zhang, Jennifer Ahern, Mark J. van der Laan, Oleg Sofrygin: tmleCommunity: A R Package Implementing Target Maximum Likelihood Estimation for Community-level Data (2020) arXiv
  3. Luedtke, Alex; Carone, Marco; Van der Laan, Mark J.: An omnibus non-parametric test of equality in distribution for unknown functions (2019)
  4. Van der Laan, Mark J.; Rose, Sherri: Targeted learning in data science. Causal inference for complex longitudinal studies (2018)
  5. Díaz, Iván: Efficient estimation of quantiles in missing data models (2017)
  6. Frölich, Markus; Huber, Martin; Wiesenfarth, Manuel: The finite sample performance of semi- and non-parametric estimators for treatment effects and policy evaluation (2017)
  7. Johan Steen and Tom Loeys and Beatrijs Moerkerke and Stijn Vansteelandt: medflex: An R Package for Flexible Mediation Analysis using Natural Effect Models (2017) not zbMATH
  8. Samuel Lendle; Joshua Schwab; Maya Petersen; Mark van der Laan: ltmle: An R Package Implementing Targeted Minimum Loss-Based Estimation for Longitudinal Data (2017) not zbMATH
  9. Balzer, Laura; Ahern, Jennifer; Galea, Sandro; van der Laan, Mark: Estimating effects with rare outcomes and high dimensional covariates: knowledge is power (2016)
  10. Biau, Gérard; Fischer, Aurélie; Guedj, Benjamin; Malley, James D.: COBRA: a combined regression strategy (2016)
  11. Tran, Linh; Yiannoutsos, Constantin T.; Musick, Beverly S.; Wools-Kaloustian, Kara K.; Siika, Abraham; Kimaiyo, Sylvester; van der Laan, Mark J.; Petersen, Maya: Evaluating the impact of a HIV low-risk express care task-shifting program: a case study of the targeted learning roadmap (2016)
  12. Sapp, Stephanie; van der Laan, Mark J.; Canny, John: Subsemble: an ensemble method for combining subset-specific algorithm fits (2014)
  13. Schnitzer, Mireille E.; Van der Laan, Mark J.; Moodie, Erica E. M.; Platt, Robert W.: Effect of breastfeeding on gastrointestinal infection in infants: a targeted maximum likelihood approach for clustered longitudinal data (2014)
  14. Stephan Ritter; Nicholas Jewell; Alan Hubbard: R Package multiPIM: A Causal Inference Approach to Variable Importance Analysis (2014) not zbMATH
  15. Gruber, Susan; Van der Laan, Mark J.: An application of targeted maximum likelihood estimation to the meta-analysis of safety data (2013)
  16. Lendle, Samuel D.; Subbaraman, Meenakshi S.; van der Laan, Mark J.: Identification and efficient estimation of the natural direct effect among the untreated (2013)
  17. Chambaz, Antoine; Neuvial, Pierre; van der Laan, Mark J.: Estimation of a non-parametric variable importance measure of a continuous exposure (2012)
  18. LeDell, Erin; Prabhat; Zubarev, Dmitry Yu.; Austin, Brian; Lester, William A. jun.: Classification of nodal pockets in many-electron wave functions via machine learning (2012)
  19. Susan Gruber; Mark Laan: tmle: An R Package for Targeted Maximum Likelihood Estimation (2012) not zbMATH