This is the current version of the Online SuperLearner for Time-Series data R package. Note that this version is in active development, and considered to be pre-alpha software. Be very careful interpretting any results from this package.


  • Automatic optimal predictor ensembling via sequential cross-validatio.
  • Can be extended with several algorithms.
  • Has several pre-defined summary measures

Install the development version from GitHub:

# install.packages("devtools")


For an example on how to run the OnlineSuperLearner, view the Jupyter notebook, or the R/OnlineSuperLearner.Simulation.R file. For a complete guide see the documentation.

You can also run the demos for the project. Run:

demo('cpp-demo', package = 'OnlineSuperLearner')


  • View the issues page


Polley EC, van der Laan MJ (2010) Super Learner in Prediction. U.C. Berkeley Division of Biostatistics Working Paper Series. Paper 226.

van der Laan, M. J., Polley, E. C. and Hubbard, A. E. (2007) Super Learner. Statistical Applications of Genetics and Molecular Biology, 6, article 25.

van der Laan, M. J., & Rose, S. (2011). Targeted learning: causal inference for observational and experimental data. Springer Science & Business Media.

Benkeser, D., Ju, C., Lendle, S. D., & van der Laan, M. J. (2016). Online Cross-Validation-Based Ensemble Learning. U.C. Berkeley Division of Biostatistics Working Paper Series, Paper 355.