Package: cencrne Title: Consistent Estimation of the Number of Communities via Regularized Network Embedding Version: 1.0.0 Authors@R: c(person("Mingyang", "Ren", email = "renmingyang17@mails.ucas.ac.cn", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8061-9940")), person("Sanguo", "Zhang", role = c("aut")), person("Junhui", "Wang", role = c("aut"))) 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, . License: GPL-2 Encoding: UTF-8 Imports: MASS, Matrix LazyData: true LazyLoad: yes RoxygenNote: 7.1.2 Depends: R (>= 3.5.0) Suggests: knitr, rmarkdown VignetteBuilder: knitr, rmarkdown NeedsCompilation: no Packaged: 2026-07-04 09:16:26 UTC; root Author: Mingyang Ren [aut, cre] (), Sanguo Zhang [aut], Junhui Wang [aut] Maintainer: Mingyang Ren Repository: https://cran.r-universe.dev Date/Publication: 2023-01-09 09:00:05 UTC RemoteUrl: https://github.com/cran/cencrne RemoteRef: HEAD RemoteSha: 0e660b01a22d4ca7b4e9cd3b31f8affbc3899f84