Citations

jaxgam is a Python port of Simon Wood's mgcv R package. The statistical methods are entirely his work. If you use jaxgam, please cite the relevant mgcv papers.

References

GAM method (REML/ML estimation)

Wood SN (2011). "Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models." Journal of the Royal Statistical Society (B), 73(1), 3--36. doi:10.1111/j.1467-9868.2010.00749.x

Beyond exponential family

Wood SN, Pya N, Säfken B (2016). "Smoothing parameter and model selection for general smooth models (with discussion)." Journal of the American Statistical Association, 111, 1548--1575. doi:10.1080/01621459.2016.1180986

GCV-based model method and basics of GAMM

Wood SN (2004). "Stable and efficient multiple smoothing parameter estimation for generalized additive models." Journal of the American Statistical Association, 99(467), 673--686. doi:10.1198/016214504000000980

Overview

Wood SN (2017). Generalized Additive Models: An Introduction with R, 2 edition. Chapman and Hall/CRC.

Thin plate regression splines

Wood SN (2003). "Thin-plate regression splines." Journal of the Royal Statistical Society (B), 65(1), 95--114. doi:10.1111/1467-9868.00374

BibTeX

@Article{wood2011,
  title = {Fast stable restricted maximum likelihood and marginal
    likelihood estimation of semiparametric generalized linear models},
  journal = {Journal of the Royal Statistical Society (B)},
  volume = {73},
  number = {1},
  pages = {3--36},
  year = {2011},
  author = {S. N. Wood},
  doi = {10.1111/j.1467-9868.2010.00749.x},
}

@Article{wood2016,
  title = {Smoothing parameter and model selection for general smooth
    models (with discussion)},
  author = {S. N. Wood and N. Pya and B. S{\"a}fken},
  journal = {Journal of the American Statistical Association},
  year = {2016},
  pages = {1548--1575},
  volume = {111},
  doi = {10.1080/01621459.2016.1180986},
}

@Article{wood2004,
  title = {Stable and efficient multiple smoothing parameter estimation
    for generalized additive models},
  journal = {Journal of the American Statistical Association},
  volume = {99},
  number = {467},
  pages = {673--686},
  year = {2004},
  author = {S. N. Wood},
  doi = {10.1198/016214504000000980},
}

@Book{wood2017,
  title = {Generalized {A}dditive {M}odels: An Introduction with {R}},
  year = {2017},
  author = {S. N. Wood},
  edition = {2},
  publisher = {Chapman and Hall/CRC},
}

@Article{wood2003,
  title = {Thin-plate regression splines},
  journal = {Journal of the Royal Statistical Society (B)},
  volume = {65},
  number = {1},
  pages = {95--114},
  year = {2003},
  author = {S. N. Wood},
  doi = {10.1111/1467-9868.00374},
}

Machine-readable citation

See CITATION.cff for machine-readable citation metadata. GitHub renders a "Cite this repository" button from this file.

License

jaxgam is licensed under the GPL-2.0-or-later, matching mgcv's GPL (>= 2) license. As a derivative work of mgcv, this ensures downstream users have the same freedoms granted by the original package.