{"id":16489800,"url":"https://github.com/leifeld/btergm","last_synced_at":"2025-03-21T07:31:36.245Z","repository":{"id":62459037,"uuid":"74115002","full_name":"leifeld/btergm","owner":"leifeld","description":"Temporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood","archived":false,"fork":false,"pushed_at":"2024-03-31T21:13:05.000Z","size":747,"stargazers_count":16,"open_issues_count":3,"forks_count":10,"subscribers_count":4,"default_branch":"master","last_synced_at":"2024-10-12T13:45:22.712Z","etag":null,"topics":["complex-networks","dynamic-analysis","ergm","estimation","goodness-of-fit","inference","longitudinal-data","network-analysis","prediction","tergm"],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/leifeld.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2016-11-18T09:26:50.000Z","updated_at":"2024-02-18T14:44:23.000Z","dependencies_parsed_at":"2022-11-02T00:45:21.030Z","dependency_job_id":"e0e75eb4-4979-4e84-8854-0abe0a8b2743","html_url":"https://github.com/leifeld/btergm","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/leifeld%2Fbtergm","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/leifeld%2Fbtergm/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/leifeld%2Fbtergm/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/leifeld%2Fbtergm/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/leifeld","download_url":"https://codeload.github.com/leifeld/btergm/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":221812895,"owners_count":16884717,"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","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":["complex-networks","dynamic-analysis","ergm","estimation","goodness-of-fit","inference","longitudinal-data","network-analysis","prediction","tergm"],"created_at":"2024-10-11T13:45:28.011Z","updated_at":"2024-10-28T09:36:29.644Z","avatar_url":"https://github.com/leifeld.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# btergm\n\nTemporal Exponential Random Graph Models by Bootstrapped Pseudolikelihood.\n\nTemporal Exponential Random Graph Models (TERGM) estimated by maximum pseudolikelihood with bootstrapped confidence intervals or Markov Chain Monte Carlo maximum likelihood (MCMC MLE). Goodness of fit assessment for ERGMs, TERGMs, and SAOMs. Micro-level interpretation of ERGMs and TERGMs.\n\n[![R-CMD-check](https://github.com/leifeld/btergm/actions/workflows/check-standard.yaml/badge.svg)](https://github.com/leifeld/btergm/actions/workflows/check-standard.yaml)\n[![test-coverage](https://github.com/leifeld/btergm/actions/workflows/test-coverage.yaml/badge.svg)](https://github.com/leifeld/btergm/actions/workflows/test-coverage.yaml)\n[![coverage status](https://codecov.io/gh/leifeld/btergm/branch/master/graph/badge.svg)](https://codecov.io/github/leifeld/btergm?branch=master)\n\n# Installation\n\nThe last stable release can be installed from CRAN:\n```r\ninstall.packages(\"btergm\")\n```\nTo install the latest development version from GitHub, use the remotes package:\n```r\nremotes::install_github(\"leifeld/btergm\")\n```\n\n[![cran version](http://www.r-pkg.org/badges/version/btergm)](https://cran.r-project.org/package=btergm)\n[![downloads](http://cranlogs.r-pkg.org/badges/btergm)](http://cranlogs.r-pkg.org/badges/btergm)\n[![total downloads](http://cranlogs.r-pkg.org/badges/grand-total/btergm)](http://cranlogs.r-pkg.org/badges/grand-total/btergm)\n[![research software impact](http://depsy.org/api/package/cran/btergm/badge.svg)](http://depsy.org/package/r/btergm)\n\n# Documentation\nDocumentation of the package is available as a JStatSoft article:\n\nLeifeld, Philip, Skyler J. Cranmer and Bruce A. Desmarais (2018): Temporal Exponential Random Graph Models with btergm: Estimation and Bootstrap Confidence Intervals. _Journal of Statistical Software_ 83(6): 1-36. https://doi.org/10.18637/jss.v083.i06.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fleifeld%2Fbtergm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fleifeld%2Fbtergm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fleifeld%2Fbtergm/lists"}