locCorotGrupos: Parameters for cluster mapping
In RMacoqui: Identifying and describing chorotypes based on similarity between species distributions

Description Usage Arguments Details Value Note Author(s) See Also Examples

This function provides ways for cluster mapping. For each locality (lines in data), values of four parameters are given. Pi: Presence of the cluster i (presence/absence of at least one species of the cluster); SRi: Species Richness of the cluster i (number of species of the cluster); MMDi: Maximum Membership Degree-of any species-in the cluster i (fuzzy version of Pi); FSRi: Fuzzy Species Richness (fuzzy version of SRi, i.e sum of all species' degree of membership in the cluster i).

1	locCorotGrupos(fuzzyres, grupos)

`fuzzyres`	object resulting from function `fuzzy.Clusters`
`grupos`	dendrogram clusters-identified by the analyst-on which the analysis is focused (see `fuzzy.Clusters`)

Before applying locCorotGrupos, fuzzy.Clusters must be run, and outputs stored as object fuzzyres.

Function locCorotGrupos currently only works if fuzzy.Clusters was run with an object (macoquires) which resulted from executing macoqui with a presences/absences data set.

This function returns the input list (invisibly), with one added element which is also shown in the console:

locGrupos

locality identification (correlative numbers starting in 1 are given to rows in data); Pi, SRi, MMDi and FSRi values of every cluster i in each locality

This function can take some computing time for large data sets.

Jesus Olivero, Ramon Hidalgo, Ana L. Marquez, A. Marcia Barbosa, Raimundo Real

fuzzy.Clusters, ver.matRmacoqui

data(amphib)
macoquires <- macoqui(amphib)
grupos <- c(12,1,12,2,13,1,13,2,15,1,10,1,10,2,17,2)
fuzzyres <- fuzzy.Clusters(macoquires, grupos)
fuzzylocs <- locCorotGrupos(fuzzyres, grupos)