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:: Agglomerative Nesting (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 agglomerative nesting (hierarchical clustering) of a multivariate dataset as proposed by Kaufman and Rousseeuw. At each level the two nearest clusters are merged to form the next cluster.
This procedure computes the 'agglomerative coefficient' which can be interpreted as the amount of clustering structure that has been found. In addition, this procedure generates the so-called banner display.
The following clustering methods are currently supported: unweighted pair-group average, single linkage, complete linkage, Ward's method, weighted average linkage, and the 'flexible' method based on the Lance-Williams formula.

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:
Sample Range:
(leave blank to include all observations)
From:
To:
Metric 
Method 
Number of parameters in Lance-Williams formula 
alpha 1 (Lance-Williams formula) 
alpha 2 (Lance-Williams formula) 
beta (Lance-Williams formula) 
gamma (Lance-Williams formula) 
Chart options
Width:
Height:
Title:
Label y-axis:
Label x-axis:







Click here to edit the underlying code of this R Module.

Source code of R module
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Cite this software as:
Wessa, P., (2012), Agglomerative Nesting (v1.0.3) in Free Statistics Software (v1.1.23-r7), Office for Research Development and Education, URL http://www.wessa.net/rwasp_agglomerativehierarchicalclustering.wasp/
The R code is based on :
Kaufman, L. and Rousseeuw, P.J. (1990). Finding Groups in Data: An Introduction to Cluster Analysis, Wiley, New York.
Anja Struyf, Mia Hubert & Peter J. Rousseeuw (1996): Clustering in an Object-Oriented Environment. Journal of Statistical Software, nr 1. URL: http://www.stat.ucla.edu/journals/jss/
Struyf, A., Hubert, M. and Rousseeuw, P.J. (1997). Integrating Robust Clustering Techniques in S-PLUS, Computational Statistics and Data Analysis, nr 26, 17-37
Lance, G.N., and W.T. Williams (1966). A General Theory of Classifactory Sorting Strategies, I. Hierarchical Systems, Computer J., nr 9, 373-380
Top | Output | Charts | References | History | Feedback
Last computationDelete history
Server DateModuleCommand
Sat, 27 May 2017 08:58:25 +0100Agglomerative Nesting (Hierarchical Clustering)Print | Word | Excel | Blog this | Delete
Sat, 27 May 2017 08:58:25 +0100Start of session-
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To cite Wessa.net in publications use:
Wessa, P. (2017), Free Statistics Software, Office for Research Development and Education,
version 1.1.23-r7, URL http://www.wessa.net/

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Software Version : 1.1.23-r7
Algorithms & Software : Patrick Wessa, PhD
Server : wessa.net

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