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rSpectral
View on CRAN: Click
here
Download and install rSpectral package within the R console
Install from CRAN:
install.packages("rSpectral")
Install from Github:
library("remotes")
install_github("cran/rSpectral") Install by package version:
library("remotes")
install_version("rSpectral", "1.0.0.14") Attach the package and use:
library("rSpectral")
Maintained by
Anatoly Sorokin
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-08-19
Latest Update: 2025-09-03
Description:
Implements the network clustering algorithm described in
Newman (2006) . The complete
iterative algorithm comprises of two steps. In the first step, the
network is expressed in terms of its leading eigenvalue and
eigenvector and recursively partition into two communities.
Partitioning occurs if the maximum positive
eigenvalue is greater than the tolerance (10e-5) for the current
partition, and if it results in a positive contribution to the
Modularity.
Given an initial separation using the leading eigen step, 'rSpectral'
then continues to maximise for the change in Modularity using a
fine-tuning step - or variate thereof. The first stage here is to
find the node which, when moved from one community to another,
gives the maximum change in Modularity. This node
How to cite:
Anatoly Sorokin (2022). rSpectral: Spectral Modularity Clustering. R package version 1.0.0.14, https://cran.r-project.org/web/packages/rSpectral. Accessed 05 Mar. 2026.
Other packages that cited rSpectral R package
View rSpectral citation profile
Other R packages that rSpectral depends,
imports, suggests or enhances
Complete documentation for rSpectral
Functions, R codes and Examples using
the rSpectral R package
Some associated functions: rSpectral . spectral_graphNEL . spectral_igraph_communities . spectral_igraph_membership .
Some associated R codes: RcppExports.R . graphNEL.R . igraph.R . rSpectral-package.R . Full rSpectral package functions and examples
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