{"id":35153418,"url":"https://github.com/levisc8/ipmr_esa","last_synced_at":"2026-05-22T07:35:10.600Z","repository":{"id":49257256,"uuid":"362127559","full_name":"levisc8/ipmr_esa","owner":"levisc8","description":"Materials for the ipmr workshop at ESA 2021","archived":false,"fork":false,"pushed_at":"2021-07-13T15:18:13.000Z","size":3737,"stargazers_count":1,"open_issues_count":0,"forks_count":2,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-12-31T01:52:50.967Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/levisc8.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-04-27T13:44:41.000Z","updated_at":"2024-08-24T14:42:00.000Z","dependencies_parsed_at":"2022-09-09T18:20:52.260Z","dependency_job_id":null,"html_url":"https://github.com/levisc8/ipmr_esa","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/levisc8/ipmr_esa","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/levisc8%2Fipmr_esa","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/levisc8%2Fipmr_esa/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/levisc8%2Fipmr_esa/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/levisc8%2Fipmr_esa/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/levisc8","download_url":"https://codeload.github.com/levisc8/ipmr_esa/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/levisc8%2Fipmr_esa/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33333540,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-21T12:23:38.849Z","status":"online","status_checked_at":"2026-05-22T02:00:06.671Z","response_time":265,"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":[],"created_at":"2025-12-28T16:06:55.541Z","updated_at":"2026-05-22T07:35:10.568Z","avatar_url":"https://github.com/levisc8.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"## Materials for ESA '21 ipmr Workshop\n\nThis repository hosts the tutorials for the `ipmr` workshop from ESA 2021. Tutorials are stored in `ipmr_examples/` subfolder. To run with RStudio:\n\n1. clone this repository into a folder on your computer. \n  \n    + The easiest way is to click the green \"Code\" button in the upper right corner of this page and download a Zip file. Unzip the folder after downloading.\n\n2. Open `ipmr_esa.Rproj`.\n\n3. Open `ipmr_examples/ipmr_tutorial.rmd`. \n\n4. Click the `Run Document` button above the script pane.\n\nTo run from the R GUI, follow step 1 from above, then: \n\n2. Set your working directory to the path where the unzipped repository is.\n\n3. Run `rmarkdown::run(\"ipmr_examples/ipmr_tutorial.rmd\")`.\n\n## Prerequisites\n\nIn order to get the most out of this tutorial, you will need to be familiar with the regression modeling and when to use different link functions (e.g. Logit, Log). We also assume you are familiar with matrix population models, what a state vector is, and basic analyses like per-capita growth rates and stable state distributions. There are a variety of good publications to familiarize yourself with IPM theory and practice. [Merow et al. 2014](https://besjournals.onlinelibrary.wiley.com/doi/full/10.1111/2041-210X.12146) is a good start. Though not required for this tutorial, more advanced treatments can be found in [Ellner \u0026 Rees 2006](https://www.journals.uchicago.edu/doi/pdfplus/10.1086/499438?casa_token=hVkM-U1RHs0AAAAA:YduKcTwNVRUviS5j1soKVQ62bSTNLFN8Cx-9mQTdju4yov83XNHFJNRaXptLMfDbhQUKrWFf9HI), [Rees \u0026 Ellner 2009](https://esajournals.onlinelibrary.wiley.com/doi/10.1890/08-1474.1), and Ellner, Childs, \u0026 Rees 2016. \n\nYou will also need to install the following R packages:\n\n```\ninstall.packages(c(\"DiagrammeR\",\"learnr\", \"rlang\", \"MASS\"))\n\n```\n\nThis tutorial makes use of the latest version of `ipmr`. You'll also need either update or install it:\n\n```\ninstall.packages(\"ipmr\")\n\n```\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flevisc8%2Fipmr_esa","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flevisc8%2Fipmr_esa","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flevisc8%2Fipmr_esa/lists"}