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FSSgam  

Full Subsets Multiple Regression Using GAMs
View on CRAN: Click here


Download and install FSSgam package within the R console
Install from CRAN:
install.packages("FSSgam")

Install from Github:
library("remotes")
install_github("cran/FSSgam")

Install by package version:
library("remotes")
install_version("FSSgam", "1.2.0")



Attach the package and use:
library("FSSgam")
Maintained by
Rebecca Fisher
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-09-28
Latest Update: 2026-09-28
Description:
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>.
How to cite:
Rebecca Fisher (2026). FSSgam: Full Subsets Multiple Regression Using GAMs. R package version 1.2.0, https://cran.r-project.org/web/packages/FSSgam. Accessed 24 Oct. 2026.
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Complete documentation for FSSgam
Functions, R codes and Examples using the FSSgam R package
Full FSSgam package functions and examples
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