clustcentroid: Cluster centers of a classification In miquelcaceres/vegclust: Fuzzy Clustering of Vegetation Data

Description

Function `clustcentroid` calculates the centroid (multivariate average) coordinates of a classification. Function `clustmedoid` determines the medoid (object whose average dissimilarity to all the other objects is minimal) for each cluster in the classification.

Usage

 ```1 2``` ```clustcentroid(x, y, m = 1) clustmedoid(x, y, m = 1) ```

Arguments

 `x` Community data, a site-by-species data frame. In function `clustmedoid`, `x` can alternatively be an object of class `dist` (otherwise, the dissimilarity measure is assumed to be the Euclidean distance). `y` It can be (a) A vector indicating the cluster that each object in `x` belongs to; (b) a fuzzy/hard site-by-group matrix of membership values; (c) an object of class `vegclust` or `vegclass` `m` Fuzziness exponent, only effective when `y` is a fuzzy membership matrix.

Value

Function `clustcentroid` returns a group-by-species matrix containing species average abundance values (i.e. the coordinates of each cluster centroid). Function `clustmedoid` returns a vector of indices (medoids).

Note

In order to assign new plot record data into a predefined set of classes, one should use functions `as.vegclust` and `vegclass` instead.

Author(s)

Miquel De Cáceres, Forest Science Center of Catalonia

`as.vegclust`, `vegclass`, `vegclust`, `kmeans`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```## Loads stats library(stats) ## Loads data data(wetland) ## This equals the chord transformation ## (see also \code{\link{decostand}} in package 'vegan') wetland.chord = as.data.frame(sweep(as.matrix(wetland), 1, sqrt(rowSums(as.matrix(wetland)^2)), "/")) ## Performs a K-means clustering wetland.km = kmeans(wetland.chord, centers=3, nstart=10) ## Gets the coordinates corresponding to the centroids of KM clusters clustcentroid(wetland.chord, y=wetland.km\$cluster) ## Gets the object indices corresponding to the medoids of KM clusters clustmedoid(wetland.chord, y=wetland.km\$cluster) ```