A simple function for full-subsets multiple regression in ecology with R.

ABSTRACT: 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. Here, we describe 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 and a starting generalized additive (mixed) model fit. Main advantages include not requiring a complete model to be fit as the starting point for candidate model set construction (meaning that a greater number of predictors can potentially be explored than might be available through functions such as dredge); model sets that include interactions between

SUBMITTER: Fisher R 

PROVIDER: S-EPMC6024142 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature