SUPERLEARNER Procedure

References

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  • Dudoit, S., and van der Laan, M. J. (2005). “Asymptotics of Cross-Validated Risk Estimation in Estimator Selection and Performance Assessment.” Statistical Methodology 2:131–154.

  • Hernán, M. A., and Robins, J. M. (2020). Causal Inference: What If. Boca Raton, FL: Chapman & Hall/CRC.

  • Lane, P. W., and Nelder, J. A. (1982). “Analysis of Covariance and Standardization as Instances of Prediction.” Biometrics 38:613–621.

  • Lawless, J. F., and Singhal, K. (1978). “Efficient Screening of Nonnormal Regression Models.” Biometrics 34:318–327.

  • Naimi, A. I., and Balzer, L. B. (2018). “Stacked Generalization: An Introduction to Super Learning.” European Journal of Epidemiology 33:459–464.

  • Phillips, R. V., van der Laan, M. J., Lee, H., and Gruber, S. (2023). “Practical Considerations for Specifying a Super Learner.” International Journal of Epidemiology 52:1276–1285.

  • Van der Laan, M. J., and Dudoit, S. (2003). Unified Cross-Validation Methodology for Selection among Estimators and a General Cross-Validated Adaptive Epsilon-Net Estimator: Finite Sample Oracle Inequalities and Examples. UC Berkeley Division of Biostatistics Working Paper Series, No. 130, University of California Berkeley.

  • Van der Laan, M. J., Polley, E. C., and Hubbard, A. E. (2007). “Super Learner.” Statistical Applications in Genetics and Molecular Biology 6:25.

  • Van der Laan, M. J., and Rose, S. (2011). Targeted Learning: Causal Inference for Observational and Experimental Data. New York: Springer.

  • Van der Vaart, A. W., Dudoit, S., and van der Laan, M. J. (2006). “Oracle Inequalities for Multi-fold Cross Validation.” Statistics and Decisions 24:351–371.

  • Wolpert, D. H. (1992). “Stacked Generalization.” Neural Networks 5:241–259.

  • Zou, H., and Hastie, T. (2005). “Regularization and Variable Selection via the Elastic Net.” Journal of the Royal Statistical Society, Series B 67:301–320.

Last updated: May 14, 2026