https://github.com/m-clark/r-models

A quick reference for how to run many models in R.
https://github.com/m-clark/r-models

additive-models bayesian-models brms catwalk cluster-analysis lme4 machine-learning mgcv mixed-models mixture-model pca psych r regularization sem spatial-analysis statistical-models statistics survival-analysis time-series

Last synced: 7 months ago
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A quick reference for how to run many models in R.

• Host: GitHub
• URL: https://github.com/m-clark/r-models
• Owner: m-clark
• License: other
• Created: 2018-04-14T21:44:12.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2018-05-19T00:12:15.000Z (over 7 years ago)
• Last Synced: 2025-06-04T17:46:36.491Z (8 months ago)
• Topics: additive-models, bayesian-models, brms, catwalk, cluster-analysis, lme4, machine-learning, mgcv, mixed-models, mixture-model, pca, psych, r, regularization, sem, spatial-analysis, statistical-models, statistics, survival-analysis, time-series
• Language: R
• Homepage: https://m-clark.github.io/R-models/
• Size: 21 MB
• Stars: 13
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

          






This is a quick reference for the R modeling syntax and associated packages.  While it covers a lot of ground, it is not meant to be exhaustive, but rather, it provides an easy reference for those new to R, someone trying out an unfamiliar (but otherwise common) technique, or those just interested in a comparison to similar approaches in other environments.  It can get you quickly started with many common models and extensions.

Models covered:

GLM, other distributions and categorical outcomes, regularized models, mixed models, additive models, survival analysis, survey weighting, PCA/FA, SEM, mixture models/cluster analysis, time series, spatial models, graphical models, machine learning, Bayesian analysis, text analysis, dealing with missing data.

In addition, notable packages and recommended readings are provided.

You can find the current document [here](https://m-clark.github.io/R-models/).