AICcPermanova: Model Selection of PERMANOVA Models Using AICc
Provides tools for model selection and model averaging of PerMANOVA
models using Akaike Information Criterion corrected for small sample sizes
(AICc) and Information Theoretic criteria principles. The package is built
around the PERMANOVA analysis from the 'vegan' package and provides a
streamlined workflow for generating and comparing models, obtaining model
weights, and summarizing results using model averaging approaches. The
methods implemented in this package are based on the practical information-
theoretic approach described by Burnham, K. P. and Anderson, D. R. (2002)
(<doi:10.1007/b97636>).
| Version: |
0.0.2 |
| Imports: |
broom, car, data.table, doParallel, dplyr, foreach, furrr, future, parallel, stats, stringr, tidyr, vegan |
| Suggests: |
covr, testthat (≥ 3.0.0) |
| Published: |
2023-04-11 |
| Author: |
Derek Corcoran [aut, cre] |
| Maintainer: |
Derek Corcoran <derek.corcoran.barrios at gmail.com> |
| BugReports: |
https://github.com/Sustainscapes/AICcPerm/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/Sustainscapes/AICcPerm,
https://sustainscapes.github.io/AICcPerm/ |
| NeedsCompilation: |
no |
| CRAN checks: |
AICcPermanova results |
Documentation:
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