To cite bbqr in publications use:

Rubio Garcia F (2026). bbqr: Bayesian Quantile Regression with Lasso and Adaptive Lasso. R package version 0.1.0, https://github.com/fernandorubiogarcia/bbqr.

For the binary adaptive-lasso method (bbqr_alasso) cite:

Rubio Garcia F (2023). Bayesian adaptive lasso binary quantile regression with hybrid resampling for classification of imbalanced data. Master's thesis, Wichita State University, Dept. of Mathematics, Statistics, and Physics. https://soar.wichita.edu/entities/publication/a2f86232-4704-4ec2-b685-751e7b04ec42.

The continuous adaptive lasso (cbqr_alasso) at its default q = 1 reproduces the penalty of:

Alhamzawi R, Yu K, Benoit D (2012). “Bayesian adaptive Lasso quantile regression.” Statistical Modelling, 12(3), 279–297. doi:10.1177/1471082X1101200304.

The lasso and unpenalised samplers implement published methods. Please also cite the paper for the layer you used. Binary: Benoit and Van den Poel (2012,<doi:10.1002/jae.1216>) for penalty = "none"; Benoit, Al-Hamzawi and Yu (2013,<doi:10.1007/s00180-013-0439-0>) for penalty = "lasso". Continuous: Kozumi and Kobayashi (2011,<doi:10.1080/00949655.2010.496117>) for cbqr_none(), whose kernel is their sampler; Benoit, Al-Hamzawi and Yu (2013) for cbqr_lasso(), whose hierarchy is theirs carried over to an observed response.

Corresponding BibTeX entries:

  @Manual{,
    title = {{bbqr}: Bayesian Quantile Regression with Lasso and
      Adaptive Lasso},
    author = {Fernando {Rubio Garcia}},
    year = {2026},
    note = {R package version 0.1.0},
    url = {https://github.com/fernandorubiogarcia/bbqr},
  }

  @MastersThesis{,
    title = {Bayesian adaptive lasso binary quantile regression with
      hybrid resampling for classification of imbalanced data},
    author = {Fernando {Rubio Garcia}},
    school = {Wichita State University, Dept. of Mathematics,
      Statistics, and Physics},
    year = {2023},
    url =
      {https://soar.wichita.edu/entities/publication/a2f86232-4704-4ec2-b685-751e7b04ec42},
  }

  @Article{,
    title = {Bayesian adaptive Lasso quantile regression},
    author = {Rahim Alhamzawi and Keming Yu and Dries F. Benoit},
    journal = {Statistical Modelling},
    year = {2012},
    volume = {12},
    number = {3},
    pages = {279--297},
    doi = {10.1177/1471082X1101200304},
  }