AICcPermanova

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).

Last 30 days

This package has been downloaded 395 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 11 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 4,900 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Aug 28, 2024 with 60 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.