AICc_permanova2 {AICcPermanova} | R Documentation |
Calculate AICc for a permutational multivariate analysis of variance (PERMANOVA)
Description
#' This function calculates the Akaike's Information Criterion (AICc) for a permutational multivariate analysis of variance (PERMANOVA) model. The AICc is a modified version of the Akaike Information Criterion (AIC) that is more appropriate for small sample sizes and high-dimensional models.
Usage
AICc_permanova2(adonis2_model)
Arguments
adonis2_model |
An object of class adonis2 from the vegan package |
Details
The AICc calculation for a PERMANOVA model is:
AICc = AIC + \frac{2k(k+1)}{n-k-1}
where AIC is the Akaike Information Criterion, k is the number of parameters in the model (excluding the intercept), and n is the number of observations.
Value
A data frame with the AICc, the number of parameters (k) and the number of observations (N).
References
Zuur, A. F., Ieno, E. N., Walker, N. J., Saveliev, A. A., & Smith, G. M. (2009). Mixed effects models and extensions in ecology with R. Springer Science & Business Media.
See Also
Examples
library(vegan)
data(dune)
data(dune.env)
# Run PERMANOVA using adonis2
Model <- adonis2(dune ~ Management*A1, data = dune.env)
# Calculate AICc
AICc_permanova2(Model)