::Free Statistics and Forecasting Software::



:: Hierarchical Clustering - Free Statistics Software (Calculator) ::

All rights reserved. The non-commercial (academic) use of this software is free of charge. The only thing that is asked in return is to cite this software when results are used in publications.

This free online software (calculator) computes the hierarchical clustering of a multivariate dataset based on dissimilarities. There are various methods available:
  • Ward method (compact spherical clusters, minimizes variance)
  • Complete linkage (similar clusters)
  • Single linkage (related to minimal spanning tree)
  • Median linkage (does not yield monotone distance measures)
  • Centroid linkage (does not yield monotone distance measures)
  • Average method
  • McQuitty method

The dendrogram is always displayed. In addition, the cut tree (top clusters only) is displayed if the second parameter is specified. There is an option to display the dendrogram horizontally and another option to display triangular trees.
Note: the R output text contains a dendrogram in text format with all details.

Enter (or paste) a matrix (table) containing all data (time) series. Every column represents a different variable and must be delimited by a space or Tab. Every row represents a period in time (or category) and must be delimited by hard returns. The easiest way to enter data is to copy and paste a block of spreadsheet cells. Please, do not use commas or spaces to seperate groups of digits!

Send output to:
Data X (click to load default data)
Names of X columns:
# of (top) clusters to display 
Chart options
Label y-axis:
Label x-axis:

Source code of R module
Top | Output | Charts | References

Cite this software as:
Wessa, P., (2017), Hierarchical Clustering (v1.0.5) in Free Statistics Software (v1.2.1), Office for Research Development and Education, URL https://www.wessa.net/rwasp_hierarchicalclustering.wasp/
The R code is based on :
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988), The New S Language, Wadsworth & Brooks/Cole. (S version.)
Gordon, A. D. (1999), Classification, Second Edition. London: Chapman and Hall / CRC
Murtagh, F. (1985). Multidimensional Clustering Algorithms, in COMPSTAT Lectures 4, Wuerzburg: Physica-Verlag
McQuitty, L.L. (1966). Similarity Analysis by Reciprocal Pairs for Discrete and Continuous Data, Educational and Psychological Measurement, nr. 26, 825-831
Top | Output | Charts | References

To cite Wessa.net in publications use:
Wessa, P. (2024), Free Statistics Software, Office for Research Development and Education,
version 1.2.1, URL https://www.wessa.net/

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Software Version : 1.2.1
Algorithms & Software : Patrick Wessa, PhD
Server : www.wessa.net

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