pDist: Distances as either matrix [1:n,1:n] or dist object
ClusterNo: A number k which defines k different clusters to be built by the algorithm.
Type: Method of cluster analysis: "ward.D", "ward.D2", "single", "complete", "average", "mcquitty", "median" or "centroid".
ColorTreshold: Draws cutline w.r.t. dendogram y-axis (height), height of line as scalar should be given
Fast: If TRUE and fastcluster installed, then a faster implementation of the methods above can be used
...: In case of plotting further argument for plot, see as.dendrogram
Returns
List of - Cls: If, ClusterNo>0: [1:n] numerical vector with n numbers defining the classification as the main output of the clustering algorithm. It has k unique numbers representing the arbitrary labels of the clustering. Otherwise for ClusterNo=0: NULL
Dendrogram: Dendrogram of hierarchical clustering algorithm
Object: Ultrametric tree of hierarchical clustering algorithm