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Please cite the following works when using the 'haldensify' software package, including both the software tool and any articles describing the statistical methodology.

Hejazi N, Benkeser D, van der Laan M (2025). haldensify: Highly adaptive lasso conditional density estimation. doi:10.5281/zenodo.3698329, R package version 0.2.8, https://github.com/nhejazi/haldensify.

Hejazi N, van der Laan M, Benkeser D (2022). “haldensify: Highly adaptive lasso conditional density estimation in R.” Journal of Open Source Software. doi:10.21105/joss.04522, https://doi.org/10.21105/joss.04522.

Hejazi N, Benkeser D, Díaz I, van der Laan M (2022). “Efficient estimation of modified treatment policy effects based on the generalized propensity score.” arXiv. https://arxiv.org/abs/2205.05777.

Corresponding BibTeX entries:

  @Manual{,
    title = {{haldensify}: Highly adaptive lasso conditional density
      estimation},
    author = {Nima S Hejazi and David Benkeser and Mark J {van der
      Laan}},
    year = {2025},
    note = {R package version 0.2.8},
    doi = {10.5281/zenodo.3698329},
    url = {https://github.com/nhejazi/haldensify},
  }
  @Article{,
    title = {{haldensify}: Highly adaptive lasso conditional density
      estimation in {R}},
    author = {Nima S Hejazi and Mark J {van der Laan} and David
      Benkeser},
    year = {2022},
    journal = {Journal of Open Source Software},
    publisher = {The Open Journal},
    doi = {10.21105/joss.04522},
    url = {https://doi.org/10.21105/joss.04522},
  }
  @Article{,
    title = {Efficient estimation of modified treatment policy effects
      based on the generalized propensity score},
    author = {Nima S Hejazi and David Benkeser and Iván Díaz and Mark J
      {van der Laan}},
    year = {2022},
    journal = {arXiv},
    url = {https://arxiv.org/abs/2205.05777},
  }

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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