{"id":13400016,"url":"https://github.com/noamross/gam-resources","last_synced_at":"2025-08-25T13:13:13.965Z","repository":{"id":139788260,"uuid":"110888959","full_name":"noamross/gam-resources","owner":"noamross","description":null,"archived":false,"fork":false,"pushed_at":"2020-12-17T13:06:42.000Z","size":7883,"stargazers_count":189,"open_issues_count":0,"forks_count":29,"subscribers_count":12,"default_branch":"master","last_synced_at":"2024-07-31T19:23:17.369Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"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/noamross.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,"roadmap":null,"authors":null}},"created_at":"2017-11-15T21:32:52.000Z","updated_at":"2024-07-24T16:07:12.000Z","dependencies_parsed_at":"2023-05-13T12:15:50.591Z","dependency_job_id":null,"html_url":"https://github.com/noamross/gam-resources","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/noamross%2Fgam-resources","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/noamross%2Fgam-resources/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/noamross%2Fgam-resources/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/noamross%2Fgam-resources/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/noamross","download_url":"https://codeload.github.com/noamross/gam-resources/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246837685,"owners_count":20841903,"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":[],"created_at":"2024-07-30T19:00:46.575Z","updated_at":"2025-04-02T15:13:01.587Z","avatar_url":"https://github.com/noamross.png","language":null,"funding_links":[],"categories":["Others"],"sub_categories":[],"readme":"# Resources for Learning About and Using GAMs in R\n\nIn no particular order:\n\n-  [Generalized Additive Models in R: A Free Interactive Course](https://noamross.github.io/gams-in-r-course/), by me. A friendly introduction requiring only basic knowledge of R and linear regression.  4-5 hours of slides and interactive exercises.  This was formerly on a commercial platform but is now open source.\n-  [Slides from my talk at the New York R User's Group](2017-11-14-noamross-gams-nyhackr.pdf) (this repo).  This is a high-level overview of things that GAMs and mgcv can do.  Video (~80 minutes) here: \u003chttps://www.youtube.com/watch?v=q4_t8jXcQgc\u003e\n-  Materials from our [2017 Ecological Society of America workshop on GAMs](https://noamross.github.io/mgcv-esa-workshop/).  These are designed for the interactive workshop but may still be useful.  Target audience is graduate students with a little more statistical training. GLM knowledge a prerequisite. More material on inference, theory and more exotic distributions. See the [references page](https://noamross.github.io/mgcv-esa-2018/links_and_bibliography.html) in particular\n    -   The [2018 materials](https://noamross.github.io/mgcv-esa-2018/) are almost exactly the same, but we are tracking issues in that repo for future improvement!\n-  [Gavin Simpson's ~3 hour YouTube introduction to GAMs](https://www.youtube.com/watch?v=sgw4cu8hrZM) covers much of the same material as my course in one long lecture, with different examples and some updates as of summer 2020.\n-  The essential GAMs reference is Simon Wood's [Generalized Additive Models in R](https://www.crcpress.com/Generalized-Additive-Models-An-Introduction-with-R-Second-Edition/Wood/p/book/9781498728331).  \n    -  Recently reviewed by Virgilio Gomez-Rubio in the [Journal of Statistical Software](https://www.jstatsoft.org/article/view/v086b01)\n-  [An online book](https://m-clark.github.io/generalized-additive-models/) by Michael Clark gives an a very nice short introduction to both GAM theory and use in R.\n-  Gavin Simpsons's excellent, [GAM-centric blog](https://www.fromthebottomoftheheap.net/) where he tries out new and little-used GAM formulations.\n-  [StackOverflow](https://stackoverflow.com/questions/tagged/mgcv) and [Cross Validated](https://stats.stackexchange.com/questions/tagged/mgcv) tags for `mgcv`\n    -  Home to Gavin's amazing [Cross Validated answer on spatiotemporal modelling with GAMs](https://stats.stackexchange.com/questions/244042/trend-in-irregular-time-series-data/306361#306361)\n-  [A post by Kim Larsen's GAMs on the Stitchfix Blog](http://multithreaded.stitchfix.com/blog/2015/07/30/gam/) which explains GAMs and compares them to other methods for classification.\n-  The [**gratia**](https://github.com/gavinsimpson/gratia) package by Gavin Simpson for using **mgcv** with **ggplot2** and other useful and tidy helper functions, such as calculating spline derivatives and simulating from model posteriors.  Here's a [blog post](https://www.fromthebottomoftheheap.net/2018/10/23/introducing-gratia/) introducing it.\n-  [Hierarchical Generalized Additive Models: an introduction with mgcv](https://peerj.com/articles/6876/) A paper by Eric J. Pedersen, David L. Miller, Gavin Simpson, and Noam Ross on fitting gams with heirarchical/mixed structures.  [GitHub repo here](https://github.com/noamross/mixed-effect-gams).\n-  [Modelling palaeoecological time series using generalized additive models](https://www.biorxiv.org/content/early/2018/05/15/322248), a paper by Gavin L. Simpson\n- [Bayesian views of generalized additive modelling](https://arxiv.org/abs/1902.01330), a brief but useful write-up on Bayesian approaches and interpretations of GAMs by Dave Miller.\n- [Generalised additive mixed models for dynamic analysis in linguistics: a practical introduction](https://arxiv.org/abs/1703.05339) by [Márton Sóskuthy](https://twitter.com/msoskuthy)\n- [Simplified Integrated Nested Laplace Approximation](https://people.maths.bris.ac.uk/~sw15190/ginlane.pdf) by Simon N. Wood, details the `ginla()` function added in **mgcv** 1.8-27.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnoamross%2Fgam-resources","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnoamross%2Fgam-resources","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnoamross%2Fgam-resources/lists"}