{ "_id": "6abb206199f7aa8c6aa43351", "Package": "FSSgam", "Title": "Full Subsets Multiple Regression Using GAMs", "Version": "1.2.0.9000", "Authors@R": "c(\nperson(\"Rebecca\", \"Fisher\",\nemail = \"r.fisher@aims.gov.au\",\nrole = c(\"aut\", \"cre\")),\nperson(\"Australian Institute of Marine Science\",\nrole = \"cph\")\n)", "Description": "Full-subsets information-theoretic approaches are\nincreasingly used to explore predictive power and variable\nimportance when a wide range of candidate predictors are being\nconsidered. This package provides functions that can be used to\nconstruct, fit, and compare a complete model set of possible\necological or environmental predictors for a given response\nvariable of interest. Models are based on Generalized Additive\nModels (GAMs) and build on the 'MuMIn' package. Advantages\ninclude the capacity to fit more predictors than there are\nreplicates, automatic removal of models with correlated\npredictors, and support for model sets that include\ninteractions between factors and smooth predictors, as well as\nsmooth-by-smooth interactions via te(). Methods are described\nin Fisher et al. (2018) .", "License": "Apache License (== 2.0)", "Encoding": "UTF-8", "LazyData": "true", "URL": "https://github.com/beckyfisher/FSSgam_package,\nhttps://beckyfisher.github.io/FSSgam_package/,\nhttps://beckyfisher.github.io/FSSgam/", "BugReports": "https://github.com/beckyfisher/FSSgam_package/issues", "Config/testthat/edition": "3", "Config/roxygen2/version": "8.0.0", "Repository": "https://beckyfisher.r-universe.dev", "Date/Publication": "2026-09-29 01:55:43 UTC", "RemoteUrl": "https://github.com/beckyfisher/fssgam_package", "RemoteRef": "HEAD", "RemoteSha": "d32db19303bdbf12321635d9e6d4ada8704e1634", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-29 02:15:03 UTC", "User": "root" }, "Author": "Rebecca Fisher [aut, cre],\nAustralian Institute of Marine Science [cph]", "Maintainer": "Rebecca Fisher ", "_user": "beckyfisher", "_type": "src", "_file": "FSSgam_1.2.0.9000.tar.gz", "_fileid": 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