FSSgam: Full Subsets Multiple Regression Using GAMs

Full-subsets information-theoretic approaches are increasingly used to explore predictive power and variable importance when a wide range of candidate predictors are being considered. This package provides functions that can be used to construct, fit, and compare a complete model set of possible ecological or environmental predictors for a given response variable of interest. Models are based on Generalized Additive Models (GAMs) and build on the 'MuMIn' package. Advantages include the capacity to fit more predictors than there are replicates, automatic removal of models with correlated predictors, and support for model sets that include interactions between factors and smooth predictors, as well as smooth-by-smooth interactions via te(). Methods are described in Fisher et al. (2018) <doi:10.1002/ece3.4134>.

Version:	1.2.0
Depends:	R (≥ 4.4.0)
Imports:	doSNOW, foreach, mgcv, MuMIn, nnet, parallel, stats, utils
Suggests:	covr, gamm4, Matrix, testthat (≥ 3.2.0)
Published:	2026-09-28
DOI:	10.32614/CRAN.package.FSSgam
Author:	Rebecca Fisher [aut, cre], Australian Institute of Marine Science [cph]
Maintainer:	Rebecca Fisher <r.fisher at aims.gov.au>
BugReports:	https://github.com/beckyfisher/FSSgam_package/issues
License:	Apache License (== 2.0)
URL:	https://github.com/beckyfisher/FSSgam_package, https://beckyfisher.github.io/FSSgam_package/, https://beckyfisher.github.io/FSSgam/
NeedsCompilation:	no
Materials:	README, NEWS
CRAN checks:	FSSgam results

Documentation:

Reference manual:

FSSgam.html , FSSgam.pdf

Downloads:

Package source:	FSSgam_1.2.0.tar.gz
Windows binaries:	r-devel: FSSgam_1.2.0.zip, r-release: FSSgam_1.2.0.zip, r-oldrel: FSSgam_1.2.0.zip
macOS binaries:	r-release (arm64): FSSgam_1.2.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

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