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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "gdam" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'gdam: Fast Robust Additive Models using Gamma Divergence'
version: 0.0.1
doi: 10.32614/CRAN.package.gdam
abstract: Provides a computationally efficient method (at least at the time of development!)
  for robust additive modeling based on the gamma divergence, implementing the methodology
  of Hui, Ding, and Sugasawa (2026) <https://doi.org/10.1007/s11222-026-10960-3>.
  The method assumes an identity link and normally distributed errors, and applies
  the gamma divergence to the resulting restricted maximum likelihood function so
  as to obtain a loss function that is less sensitive to outlying responses. Because
  'gdam' uses a model fitted via the 'mgcv' package as the starting point for optimization,
  and leverages many of its existing techniques for estimation and inference, users
  can take advantage of many of the smoothing options available in the 'mgcv' package
  for constructing additive models.
authors:
- family-names: Hui
  given-names: Francis KC
  email: fhui28@gmail.com
  orcid: https://orcid.org/0000-0003-0765-3533
repository: https://fhui28.r-universe.dev
repository-code: https://github.com/fhui28/gdam
commit: bd330583b2b57ecc7b3919d05b0741068d13059b
url: https://github.com/fhui28/gdam
date-released: '2026-09-10'
contact:
- family-names: Hui
  given-names: Francis KC
  email: fhui28@gmail.com
  orcid: https://orcid.org/0000-0003-0765-3533