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cencrne  

Consistent Estimation of the Number of Communities via Regularized Network Embedding
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("cencrne", "1.0.0")



Attach the package and use:
library("cencrne")
Maintained by
Mingyang Ren
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-01-09
Latest Update: 2023-01-09
Description:
The network analysis plays an important role in numerous application domains including biomedicine. Estimation of the number of communities is a fundamental and critical issue in network analysis. Most existing studies assume that the number of communities is known a priori, or lack of rigorous theoretical guarantee on the estimation consistency. This method proposes a regularized network embedding model to simultaneously estimate the community structure and the number of communities in a unified formulation. The proposed model equips network embedding with a novel composite regularization term, which pushes the embedding vector towards its center and collapses similar community centers with each other. A rigorous theoretical analysis is conducted, establishing asymptotic consistency in terms of community detection and estimation of the number of communities. Reference: Ren, M., Zhang S. and Wang J. (2022). "Consistent Estimation of the Number of Communities via Regularized Network Embedding". Biometrics, .
How to cite:
Mingyang Ren (2023). cencrne: Consistent Estimation of the Number of Communities via Regularized Network Embedding. R package version 1.0.0, https://cran.r-project.org/web/packages/cencrne
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