To cite lingamr in publications use:

Morimoto O (2026). lingamr: LiNGAM Algorithms for Causal Discovery. R package version 0.1.2.9000, https://CRAN.R-project.org/package=lingamr.

For the DirectLiNGAM algorithm please also cite:

Shimizu S, Inazumi T, Sogawa Y, Hyvärinen A, Kawahara Y, Washio T, Hoyer P, Bollen K (2011). “DirectLiNGAM: A Direct Method for Learning a Linear Non-Gaussian Structural Equation Model.” Journal of Machine Learning Research, 12, 1225–1248. https://www.jmlr.org/papers/v12/shimizu11a.html.

This package is based on the Python lingam package:

Ikeuchi T, Ide M, Zeng Y, Maeda T, Shimizu S (2023). “Python package for causal discovery based on LiNGAM.” Journal of Machine Learning Research, 24(14), 1–8. https://www.jmlr.org/papers/v24/21-0321.html.

Corresponding BibTeX entries:

  @Manual{,
    title = {{lingamr}: LiNGAM Algorithms for Causal Discovery},
    author = {Osamu Morimoto},
    year = {2026},
    note = {R package version 0.1.2.9000},
    url = {https://CRAN.R-project.org/package=lingamr},
  }

  @Article{,
    title = {{DirectLiNGAM}: A Direct Method for Learning a Linear
      Non-Gaussian Structural Equation Model},
    author = {Shohei Shimizu and Takanori Inazumi and Yasuhiro Sogawa
      and Aapo Hyvärinen and Yoshinobu Kawahara and Takashi Washio and
      Patrik O. Hoyer and Kenneth Bollen},
    journal = {Journal of Machine Learning Research},
    year = {2011},
    volume = {12},
    pages = {1225--1248},
    url = {https://www.jmlr.org/papers/v12/shimizu11a.html},
  }

  @Article{,
    title = {Python package for causal discovery based on {LiNGAM}},
    author = {Takashi Ikeuchi and Mayumi Ide and Yan Zeng and Takashi
      Nicholas Maeda and Shohei Shimizu},
    journal = {Journal of Machine Learning Research},
    year = {2023},
    volume = {24},
    number = {14},
    pages = {1--8},
    url = {https://www.jmlr.org/papers/v24/21-0321.html},
  }