association_hclust: Hierarchical clustering of association indices using...
In MNWeiss/aninet: Statistical Models for Animal Social Networks
association_hclust R Documentation
Hierarchical clustering of association indices using modularity
Description
An implementation of the network clustering method described by Lusseau (2007) and implemented in SOCPROG.
Usage
association_hclust(network, method = "average")
Arguments
network
A symmetric square matrix of association indices
method
The linkage method for hierarchical clustering
Details
This method works by transforming the association indices into distances (by subtracting them from 1), running hierarchical clustering as usual, and then calculating the modularity of the division at each split.
This method is currently only designed to be used with association-like indices (which have a maximum of 1).
Value
A named list containing the best modularity ("maximum_modularity"), the cophenetic clustering coefficient ("CCC"), the clustering tree ("tree"), a dataframe of cut heights and modularity ("cuts"), and merge information ("merge").
See hclust for details on manipulating and plotting trees.
MNWeiss/aninet documentation built on Jan. 31, 2023, 3:55 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
| association_hclust | R Documentation |
Hierarchical clustering of association indices using modularity
Description
An implementation of the network clustering method described by Lusseau (2007) and implemented in SOCPROG.
Usage
association_hclust(network, method = "average")
Arguments
network |
A symmetric square matrix of association indices |
method |
The linkage method for hierarchical clustering |
Details
This method works by transforming the association indices into distances (by subtracting them from 1), running hierarchical clustering as usual, and then calculating the modularity of the division at each split. This method is currently only designed to be used with association-like indices (which have a maximum of 1).
Value
A named list containing the best modularity ("maximum_modularity"), the cophenetic clustering coefficient ("CCC"), the clustering tree ("tree"), a dataframe of cut heights and modularity ("cuts"), and merge information ("merge").
See hclust for details on manipulating and plotting trees.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.