mvabund

The goal of mvabund is to provide tools for a model-based approach to the analysis of multivariate abundance data in ecology (Yi Wang et al. 2011), in particular, testing hypothesis about the community-environment association. Abundance measures include counts, presence/absence data, ordinal or biomass data.

This package includes functions for visualising data, fitting predictive models, checking model assumptions, as well as testing hypotheses about the community–environment association.

Installation

mvabund is available on CRAN and can be installed directly in R:

install.packages("mvabund")

library(mvabund)

Alternatively, you can install the development version of mvabund from GitHub with:

# install.packages("remotes")
remotes::install_github("eco-stats/mvabund")

library(mvabund)

Getting Started

We highly recommend you taking a good read of our vignette over at our website before launching into the mvabund. Alternatively, you can access the vignettes in R by:

remotes::install_github("eco-stats/mvabund", build_vignettes = TRUE)

vignette("mvabund")

Show mvabund your support

citation("mvabund")
#> To cite package 'mvabund' in publications use:
#> 
#>   Wang Y, Naumann U, Eddelbuettel D, Wilshire J, Warton D (2022).
#>   _mvabund: Statistical Methods for Analysing Multivariate Abundance
#>   Data_. R package version 4.2.1,
#>   <https://CRAN.R-project.org/package=mvabund>.
#> 
#> A BibTeX entry for LaTeX users is
#> 
#>   @Manual{,
#>     title = {mvabund: Statistical Methods for Analysing Multivariate Abundance Data},
#>     author = {Yi Wang and Ulrike Naumann and Dirk Eddelbuettel and John Wilshire and David Warton},
#>     year = {2022},
#>     note = {R package version 4.2.1},
#>     url = {https://CRAN.R-project.org/package=mvabund},
#>   }

Spot a bug?

Thanks for finding the bug! We would appreciate it if you can pop over to our Issues page and describe how to reproduce the bug!

Other resources

• Online tutorial for using mvabund for comparing species composition across different habitats
• Video introduction to mvabund

mvabund in action

Check out the list of studies that uses mvabund in their analyses here