NbClust_fanny: Calculate cluster validation metrics for FANNY method. See...

In annack84/STMdevelopment: Develop State-and-Transition Models for the Upper Colorado River Basin

Calculate cluster validation metrics for FANNY method. See NbClust::NbClust() and cluster::fanny() for more details.

Description

Calculate cluster validation metrics for FANNY method. See NbClust::NbClust() and cluster::fanny() for more details.

Usage

NbClust_fanny(
  data = NULL,
  diss = NULL,
  distance = "euclidean",
  min.nc = 2,
  max.nc = 15,
  method = NULL,
  index = "all",
  alphaBeale = 0.1,
  memb.exp = 2
)

Arguments

data	matrix or dataset
diss	dissimilarity matrix to be used. By default, diss=NULL, but if it is replaced by a dissimilarity matrix, distance should be "NULL".
distance	the distance measure to be used to compute the dissimilarity matrix. This must be one of: "euclidean", "maximum", "manhattan", "canberra", "binary", "minkowski" or "NULL". By default, distance="euclidean". If the distance is "NULL", the dissimilarity matrix (diss) should be given by the user. If distance is not "NULL", the dissimilarity matrix should be "NULL".
min.nc	minimal number of clusters, between 1 and (number of objects - 1)
max.nc	maximal number of clusters, between 2 and (number of objects - 1), greater or equal to min.nc. By default, max.nc=15
method	the cluster analysis method to be used. This should be one of: "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median", "centroid", "kmeans"
index	the index to be calculated. This should be one of : "kl", "ch", "hartigan", "ccc", "scott", "marriot", "trcovw", "tracew", "friedman", "rubin", "cindex", "db", "silhouette", "duda", "pseudot2", "beale", "ratkowsky", "ball", "ptbiserial", "gap", "frey", "mcclain", "gamma", "gplus", "tau", "dunn", "hubert", "sdindex", "dindex", "sdbw", "all" (all indices except GAP, Gamma, Gplus and Tau), "alllong" (all indices with Gap, Gamma, Gplus and Tau included).
alphaBeale	significance value for Beale's index.
memb.exp	value to pass to cluster::fanny()

Value

list containing index values, critical values, best number of clusters from each metric, and the best partitioning results

annack84/STMdevelopment documentation built on April 12, 2024, 6:46 p.m.