A set of functions to perform fuzzy clustering of vegetation data [De Caceres et al. (2010) <doi:10.1111/j.1654-1103.2010.01211.x>] and to assess ecological community ressemblance on the basis of structure and composition [De Caceres et al. (2013): <doi:10.1111/2041-210X.12116>]. This package contains functions used to perform fuzzy and hard clustering of vegetation data under different models.
The DESCRIPTION file:
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Miquel De Cáceres [aut, cre] Maintainer: Miquel De Cáceres <[email protected]>
De Caceres, M., Font, X, Oliva, F. (2010) The management of numerical vegetation classifications with fuzzy clustering methods. Journal of Vegetation Science 21 (6): 1138-1151.
De Cáceres, M., Legendre, P., & He, F. 2013. Dissimilarity measurements and the size structure of ecological communities (D. Faith, Ed.). Methods in Ecology and Evolution 4: 1167–1177.
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## Loads data data(wetland) ## This equals the chord transformation wetland.chord = as.data.frame(sweep(as.matrix(wetland), 1, sqrt(rowSums(as.matrix(wetland)^2)), "/")) ## Create noise clustering with 3 clusters. Perform 10 starts from random seeds ## and keep the best solution wetland.nc = vegclust(wetland.chord, mobileCenters=3, m = 1.2, dnoise=0.75, method="NC", nstart=10)
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