dissCqN is a small package designed to make the process of calculating
multiple or pairwise assemblage dissimilarity via the CqN
generalisation of similarity indices (Chao et al., 2008; Jost et al.,
2011) relatively straightforward and fast. Although CqN can
also be calculated using the SpadeR package
(e.g. SpadeR::SimilarityMult()
and
SpadeR::SimilarityPair())
– which generates a more comprehensive set of measures and also standard
errors/confidence intervals – the main advantage of dissCqN is it’s
simplicity and speed, when only the original empirical CqN
measures are required (and also if dissimilarity is preferred to
similarity). Everything can be accomplished with a single function,
dissCqN(),
which takes a matrix of assemblages x species as it’s first argument (or
a list of species interaction matrices, for network dissimilarity).
You can install the released version of dissCqN from
CRAN with:
install.packages("dissCqN")And the development version from GitHub with:
devtools::install_github("murphymv/dissCqN@dev")See the following vignette for a demonstration:
Chao, A., Jost, L., Chiang, S. C., Jiang, Y.-H., & Chazdon, R. L. (2008). A Two-Stage Probabilistic Approach to Multiple-Community Similarity Indices. Biometrics, 64(4), 1178–1186. https://doi.org/10/fcvn63
Jost, L., Chao, A., & Chazdon, R. L. (2011). Compositional similarity and beta diversity. In A. E. Magurran & B. J. McGill (Eds.), Biological Diversity: Frontiers in Measurement and Assessment (pp. 66–84). Oxford University Press.