Consistent Estimation of the Number of Communities via Regularized Network Embedding R package cencrne version 1.0.0 CRAN Task View: NetworkAnalysis (https://CRAN.R-project.org/view=NetworkAnalysis) 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, <doi:10.1111/biom.13815>. Software Depends: R (>= 3.5.0) Imports: MASS, Matrix Suggests: knitr, rmarkdown Mingyang Ren <renmingyang17@mails.ucas.ac.cn> Comprehensive R Archive Network (CRAN) Mingyang Ren [aut, cre] (ORCID: <https://orcid.org/0000-0002-8061-9940>), Sanguo Zhang [aut], Junhui Wang [aut] GPL-2 2023-01-09 application/tgz https://CRAN.R-project.org/package=cencrne doi:10.32614/CRAN.package.cencrne