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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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.