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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},  }

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