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NAC  

Network-Adjusted Covariates for Community Detection
View on CRAN: Click here


Download and install NAC package within the R console
Install from CRAN:
install.packages("NAC")

Install from Github:
library("remotes")
install_github("cran/NAC")

Install by package version:
library("remotes")
install_version("NAC", "0.1.0")



Attach the package and use:
library("NAC")
Maintained by
Yaofang Hu
[Scholar Profile | Author Map]
First Published: 2023-12-04
Latest Update: 2023-12-04
Description:
Incorporating node-level covariates for community detection has gained increasing attention these years. This package provides the function for implementing the novel community detection algorithm known as Network-Adjusted Covariates for Community Detection (NAC), which is designed to detect latent community structure in graphs with node-level information, i.e., covariates. This algorithm can handle models such as the degree-corrected stochastic block model (DCSBM) with covariates. NAC specifically addresses the discrepancy between the community structure inferred from the adjacency information and the community structure inferred from the covariates information. For more detailed information, please refer to the reference paper: Yaofang Hu and Wanjie Wang (2023) . In addition to NAC, this package includes several other existing community detection algorithms that are compared to NAC in the reference paper. These algorithms are Spectral Clustering On Ratios-of Eigenvectors (SCORE), network-based regularized spectral clustering (Net-based), covariate-based spectral clustering (Cov-based), covariate-assisted spectral clustering (CAclustering) and semidefinite programming (SDP).
How to cite:
Yaofang Hu (2023). NAC: Network-Adjusted Covariates for Community Detection. R package version 0.1.0, https://cran.r-project.org/web/packages/NAC. Accessed 21 Feb. 2025.
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Complete documentation for NAC
Functions, R codes and Examples using the NAC R package
Full NAC package functions and examples
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