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DESCRIPTION
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DESCRIPTION
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Package: FSSgam
Title: Full subsets multiple regresssion in R using gam(m4)
Version: 1.11
Authors@R: c(person("Rebecca", "Fisher", email = "r.fisher@aims.gov.au", role = c("aut", "cre")))
Description: Full subsets information theoretic approaches are becoming an increasingly popular tool for exploring predictive power and variable importance where a wide range of candidate predictors are being considered. This repository contains a simple function in the statistical programming language R that can be used to construct, fit and compare a complete model set of possible ecological or environmental predictors, given a response variable of interest. The function is based on Generalized Additive Models (GAM) and builds on the MuMIn package.. Advantages include the capacity to fit more predictors than there are replicates, automatic removal of models with correlated predictors, and model sets that include interactions between factors and smooth predictors, as all as smooth interactions with other smooths (via te). The function takes a range of arguments that allow control over the model set being constructed, including specifying cyclic and linear continuous predictors, specification of the smoothing algorithm used and the maximum complexity allowed for smooth terms.
Depends:
R (>= 3.3.2)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: doSNOW,
MuMIn,
gamm4,
mgcv,
nnet
Suggests: R.rsp
VignetteBuilder: R.rsp