{"id":31041737,"url":"https://github.com/stocnet/rsiena","last_synced_at":"2026-05-16T08:19:22.418Z","repository":{"id":39307534,"uuid":"268536910","full_name":"stocnet/rsiena","owner":"stocnet","description":"An R package for Simulation Investigation for Empirical Network Analysis","archived":false,"fork":false,"pushed_at":"2025-09-08T01:09:11.000Z","size":55703,"stargazers_count":115,"open_issues_count":9,"forks_count":26,"subscribers_count":13,"default_branch":"main","last_synced_at":"2025-09-08T01:14:04.016Z","etag":null,"topics":["cran","longitudinal-data","r","rsiena","social-network-analysis","statistical-network-analysis","statistics"],"latest_commit_sha":null,"homepage":"http://www.stats.ox.ac.uk/~snijders/siena/","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/stocnet.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS.md","contributing":".github/CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":".github/CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2020-06-01T13:55:59.000Z","updated_at":"2025-07-26T13:17:44.000Z","dependencies_parsed_at":"2023-10-05T13:07:44.844Z","dependency_job_id":"dd22c443-5e48-48a6-bff3-df7eb6e832e9","html_url":"https://github.com/stocnet/rsiena","commit_stats":{"total_commits":334,"total_committers":14,"mean_commits":"23.857142857142858","dds":0.625748502994012,"last_synced_commit":"51f38fd9b2042400bef5fd9b53d6e4ceafa05772"},"previous_names":["stocnet/rsiena","snlab-nl/rsiena"],"tags_count":65,"template":false,"template_full_name":null,"purl":"pkg:github/stocnet/rsiena","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stocnet%2Frsiena","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stocnet%2Frsiena/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stocnet%2Frsiena/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stocnet%2Frsiena/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/stocnet","download_url":"https://codeload.github.com/stocnet/rsiena/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stocnet%2Frsiena/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":275094398,"owners_count":25404446,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-09-14T02:00:10.474Z","response_time":75,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cran","longitudinal-data","r","rsiena","social-network-analysis","statistical-network-analysis","statistics"],"created_at":"2025-09-14T10:40:36.396Z","updated_at":"2026-02-26T17:28:10.931Z","avatar_url":"https://github.com/stocnet.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# rsiena  \u003cimg src=\"https://raw.githubusercontent.com/stocnet/rsiena/main/inst/rsienalogo-2.png\" align=\"right\" width=\"150\"/\u003e\n\n![CRAN/METACRAN](https://img.shields.io/cran/l/RSiena)\n![CRAN/METACRAN](https://img.shields.io/cran/v/RSiena)\n![GitHub R package version](https://img.shields.io/github/r-package/v/stocnet/rsiena)\n![GitHub issues](https://img.shields.io/github/issues-raw/stocnet/rsiena)\n![GitHub All Releases](https://img.shields.io/github/downloads/stocnet/rsiena/total)\n![](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)\n\n\nSIENA is a program for the statistical analysis of longitudinal network data, with the focus on social networks.\nNetworks here are understood as entire (complete) networks, not as personal (egocentered) networks: \nit is assumed that a set of nodes (social actors) is given, and all ties (links) between these nodes are known - \nexcept perhaps for a moderate amount of missing data.\n`Longitudinal` means that two or more repeated observations (\"panel data\") are available.\nThe name SIENA stands for Simulation Investigation for Empirical Network Analysis.\nThe R package is called RSiena.\n\n## Installation\n\nFor most people, the best way to install RSiena is to install the latest version from CRAN:\n\n```r\ninstall.packages(\"RSiena\")\n```\n\nThe latest binary release on GitHub will have newer features:\n\n```r\n# On Windows:\ninstall.packages(\"https://github.com/stocnet/rsiena/releases/latest/download/RSiena.zip\", repos = NULL)\n\n# On Linux\ninstall.packages(\"https://github.com/stocnet/rsiena/releases/latest/download/RSiena.tar.gz\", repos = NULL)\n\n# On Mac\ninstall.packages(\"https://github.com/stocnet/rsiena/releases/latest/download/RSiena.tgz\", repos = NULL)\n```\n\nTo compile and install the source version from GitHub, install the `{remotes}` package and then run the following. NB: this requires compilation of `C++` source files so it may take some time.\n\n```r\n# latest version\nremotes::install_github(\"stocnet/rsiena@main\")\n\n# development version\nremotes::install_github(\"stocnet/rsiena@develop\")\n```\n\n## Data types\n\nSIENA is designed for analyzing various types of data as dependent variables:\n\n### Longitudinal network data:\nThis refers to repeated measures of networks on a given node set (although it is allowed that there are some changes in the node set). Models can be specified with actor-oriented as well as tie-oriented dynamics; but mainly the former.\n\nPractical restrictions are that the number of actors should not be too large; a few hundred already is pretty large.\n\n### Longitudinal data of networks and behavior:\nThis is like longitudinal network data, but in addition there are one or more changing nodal variables that are also treated as dependent variables, and referred to as behavior. The network will influence the dynamics of the behavior, and the behavior will influence the dynamics of the network. In other words, this is about the co-evolution of networks and behavior.\n\n### Multivariate and two-mode networks:\nNetwork data sets can be multivariate, i.e., be composed of multiple networks on the same node set.\nSome or all of these networks can be two-mode networks. The restriction is that the first mode must be the same for all networks; the first mode is defined as the set of actors. The second mode node sets are allowed to differ across the various networks in a given data set. For such multivariate data sets, the model again is about the co-evolution of several networks; and this may be combined with behavior. \n\n## Manual:  \nThere is an extensive [manual](https://www.stats.ox.ac.uk/~snijders/siena/RSiena_Manual.pdf) which is complementary to the help pages in the package.\n\n## Further information...\n\nThe main Siena website is [here](http://www.stats.ox.ac.uk/~snijders/siena/). It has a lot of resources, such as scripts and papers with explanations, and lists of published applications. In future, some of these resources may be migrated to [this website](http://stocnet.github.io/rsiena/); you can find [a wiki here](https://github.com/stocnet/rsiena/wiki) that holds much of the information on the original website, including background on SAOMs and RSiena as well as links to teaching materials, literature, and contributing people and projects.\n\n## Installation\n\n### From binary\n\nPerhaps the easiest way to install RSiena is by installing a compiled binary.\nBinaries for all major OSes -- Windows, Mac, and Linux -- \ncan be found by clicking on the latest release for your OS [here](https://github.com/stocnet/rsiena/releases/latest).\nFor Windows you should use the `RSiena.zip`, for macOS it should be `RSiena.tgz`, and for Linux `RSiena.tar.gz`.\n\nOnce the file has been downloaded, install the binary appropriate for your Operating System like so:\n\n`install.packages(\"~/Downloads/RSiena.zip\", repos = NULL)`\n\namending the file suffix as necessary.\n\n### From source\n\nTo install from source the latest main version of RSiena from Github, \nplease install the `{remotes}` package from CRAN and then enter into the console:\n\n`remotes::install_github(\"stocnet/rsiena\", ref = \"main\")`\n\nThe development version of RSiena can be similarly installed as:\n\n`remotes::install_github(\"stocnet/rsiena@develop\")`\n\n## Citation\n\nTo cite the RSiena package in publications use:\n\n\u003e Ruth M. Ripley, Tom A. B. Snijders, Zsofia Boda, Andras Voros, and Paulina Preciado (2024). Manual\n\u003e for Siena version 4.0. R package version 1.4.13.\n\u003e https://www.cran.r-project.org/web/packages/RSiena/.\n\nA BibTeX entry for LaTeX users is obtained by requesting\n\n`citation(package=\"RSiena\")` \n\nin an `R` session.\n\nFor more references, see https://www.stats.ox.ac.uk/~snijders/siena/. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstocnet%2Frsiena","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstocnet%2Frsiena","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstocnet%2Frsiena/lists"}