Package: glam
Title: Generalized Additive and Linear Models (GLAM)
Version: 1.0.2
Authors@R: person("Andrew", "Cooper", email = "ahcooper@vt.edu",
  role = c("aut", "cre", "cph"))
Description: Contains methods for fitting Generalized Linear Models (GLMs) 
  and Generalized Additive Models (GAMs). Generalized regression models are
  common methods for handling data for which assuming Gaussian-distributed
  errors is not appropriate. For instance, if the response of interest is
  binary, count, or proportion data, one can instead model the expectation of
  the response based on an appropriate data-generating distribution.
  This package provides methods for fitting GLMs and GAMs under
  Beta regression, Poisson regression, Gamma regression, and Binomial regression
  (currently GLM only) settings. Models are fit using local scoring algorithms
  described in Hastie and Tibshirani (1990) <doi:10.1214/ss/1177013604>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: gam, stats
RoxygenNote: 7.3.1
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Config/testthat/edition: 3
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2024-07-07 18:11:43 UTC; Andy
Author: Andrew Cooper [aut, cre, cph]
Maintainer: Andrew Cooper <ahcooper@vt.edu>
Repository: CRAN
Date/Publication: 2024-07-09 15:40:02 UTC
Built: R 4.6.0; ; 2026-04-27 09:41:21 UTC; unix
