{ "_id": "6ab76d3299f7aa8c6aa307a8", "Package": "cencrne", "Title": "Consistent Estimation of the Number of Communities via\nRegularized Network Embedding", "Version": "1.0.0", "Authors@R": "c(person(\"Mingyang\", \"Ren\", email = \"renmingyang17@mails.ucas.ac.cn\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-8061-9940\")),\nperson(\"Sanguo\", \"Zhang\", role = c(\"aut\")),\nperson(\"Junhui\", \"Wang\", role = c(\"aut\")))", "Description": "The network analysis plays an important role in numerous\napplication domains including biomedicine. Estimation of the\nnumber of communities is a fundamental and critical issue in\nnetwork analysis. Most existing studies assume that the number\nof communities is known a priori, or lack of rigorous\ntheoretical guarantee on the estimation consistency. This\nmethod proposes a regularized network embedding model to\nsimultaneously estimate the community structure and the number\nof communities in a unified formulation. The proposed model\nequips network embedding with a novel composite regularization\nterm, which pushes the embedding vector towards its center and\ncollapses similar community centers with each other. A rigorous\ntheoretical analysis is conducted, establishing asymptotic\nconsistency in terms of community detection and estimation of\nthe number of communities. Reference: Ren, M., Zhang S. and\nWang J. (2022). \"Consistent Estimation of the Number of\nCommunities via Regularized Network Embedding\". Biometrics,\n.", "License": "GPL-2", "Encoding": "UTF-8", "LazyData": "true", "LazyLoad": "yes", "RoxygenNote": "7.1.2", "VignetteBuilder": "knitr, rmarkdown", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-26 06:55:10 UTC", "User": "root" }, "Author": "Mingyang Ren [aut, cre]\n(), Sanguo Zhang [aut],\nJunhui 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", "_user": "cran", "_type": "src", "_file": "cencrne_1.0.0.tar.gz", "_fileid": "https://r2.ropensci.org/0238ec3f78f45de47c036a9f86b3245ac15200873c255bed8d44fd8ac480d0e3", "_filesize": 1354211, "_sha256": "0238ec3f78f45de47c036a9f86b3245ac15200873c255bed8d44fd8ac480d0e3", "_expires": "2027-01-04T06:58:55.000Z", "_created": "2026-09-26T06:55:10.000Z", "_published": "2026-09-26T06:58:57.960Z", "_jobs": [ { "job": 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