Thursday, 25 September 2014

September Eco-Stats lab: model-based multivariate analysis in ecology (mvabund package and recent additions)

What does mvabund do?
Analyses multivariate data (especially abundance of presence-absence data) using simultaneous univariate models and design-based inference.

The main functions are manyglm, which fits a GLM to each response variable, and anova/summary, which use row-resampling for valid multivariate inference (i.e. taking into account correlation between variables)

Designed specially for multivariate abundance data in ecology, species-by-site stuff, which has two key properties that need to be dealt with:
(1) strong mean-variance relationship.
(2) correlation between response variables (e.g. due to species interaction)

Why is mvabund better than using PRIMER, PC-ORD, etc?
A few reasons, see this R script for details (and code to work through):