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(forthcoming) - DoubleML - An Object-Oriented Implementation of Double Machine Learning in R\"\nauthor: \"Philipp Bach\"\ndate: \"`r format(Sys.Date(), format='%b %d, %Y')`\"\noutput: github_document\n---\n\nIn this repository, we list and automatically run the simulation examples presented in [Bach et al. (forthcoming)](https://arxiv.org/abs/2103.09603)\n\n## Files for Replication of Figures and Results in DoubleML Package Vignette\n\nThe examples and results from the paper *DoubleML - An Object-Oriented Implementation of Double Machine Learning in R* can be reproduced with the R files listed in the following: \n\n1. Section 4: *Basic idea and key ingredients of double machine learning* - Code for replication of simulation examples\n    + `examples_failure_n_500_p_20.R`\n2. Section 7.8: *A short simulation study* - Code for replication of simulation results\n    + Cross-fitting: `examples_failure_n_500_p_20.R`\n    + PLR: `sim_plr.R`\n    + PLIV: `sim_plivX.R`\n    + IRM: `sim_irm.R`\n    + IIVM: `sim_IIVM.R`\n    + Merging plots: `merge_plots.R`\n    + Simultaneous inference: `sim_siminf.R`\n3. Code chunks: The reproducible code contained in the code chunks is available via\n    + `doubleml_codechunks.R`\n    + *Note*: The code in `doubleml_codechunks.R` has been automatically produced from the manuscript (`.Rmd`) using `knitr::purl()`, see also Chapter 3.4 of *Xi et al. (2020)*\n\nAll data sets and DGPs used in the paper can be replicated via corresponding functions as provided in the `DoubleML` package. The required function calls are contained in the code chunks of the paper. The API documentation is available via https://docs.doubleml.org/r/stable/reference/index.html. \n\nThe current development version of `DoubleML` is available via the GitHub repository at https://github.com/DoubleML/doubleml-for-r. The stable version can be downloaded from CRAN https://cran.r-project.org/web/packages/DoubleML/index.html.\n\nIn case you have any questions, do not hesitate to contact philipp.bach@uni-hamburg.de \n\n## Citation\n\nIf you use the DoubleML package a citation is highly appreciated:\n\nBach, P., Chernozhukov, V., Kurz, M. S., Spindler, M., and Klaassen, S. (2021), DoubleML - An Object-Oriented Implementation of Double Machine Learning in R, arXiv:2103.09603.\n\n```\n@misc{DoubleML2021R,\n  title={{DoubleML} -- {A}n Object-Oriented Implementation of Double Machine Learning in {R}},\n  author={P. Bach and V. Chernozhukov and M. S. Kurz and M. Spindler and S. Klaassen},\n  year={2021},\n  eprint={2103.09603},\n  archivePrefix={arXiv},\n  primaryClass={stat.ML},\n  note={arXiv:\\href{https://arxiv.org/abs/2103.09603}{2103.09603} [stat.ML]}\n}\n```\n\n\n## Issues, Problems, Bugs\n\nPlease report problems and bugs as [an issue in this repository.](https://github.com/PhilippBach/DoubleMLReplicationCode/issues)\n\n\n## Acknowledgements\n\nWe would like to thank Simon Couch for providing [a detailed blogpost on how to use GitHub Actions for running R scripts.]( https://blog--simonpcouch.netlify.app/blog/r-github-actions-commit/). This blogpost was used to set up the GitHub Actions used for automated replication of the simulation results.\n\n\n## References\n\nBach, P., Chernozhukov, V., Kurz, M. S., Spindler, M. and Klaassen, S. (2021), DoubleML - An Object-Oriented Implementation of Double Machine Learning in R, arXiv:2104.03220.\n\nXie, Y., Dervieux, C., \u0026 Riederer, E. (2020). R markdown cookbook. CRC Press.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdoubleml%2Fdoublemlreplicationcode","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdoubleml%2Fdoublemlreplicationcode","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdoubleml%2Fdoublemlreplicationcode/lists"}