https://github.com/jbris/stan-docker

A Docker image to run Stan, rstanarm, and brms for Bayesian statistical modelling
https://github.com/jbris/stan-docker

bayesian-inference bayesian-statistics bayesplot brms data-science docker docker-compose docker-image dockerfile probabilistic-programming r rstan rstanarm stan statistics tidybayes tidyverse

Last synced: about 1 month ago
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A Docker image to run Stan, rstanarm, and brms for Bayesian statistical modelling

• Host: GitHub
• URL: https://github.com/jbris/stan-docker
• Owner: JBris
• License: mit
• Created: 2022-07-27T14:24:37.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-07-27T14:52:58.000Z (over 2 years ago)
• Last Synced: 2023-03-08T04:41:45.720Z (almost 2 years ago)
• Topics: bayesian-inference, bayesian-statistics, bayesplot, brms, data-science, docker, docker-compose, docker-image, dockerfile, probabilistic-programming, r, rstan, rstanarm, stan, statistics, tidybayes, tidyverse
• Language: Dockerfile
• Homepage:
• Size: 6.84 KB
• Stars: 2
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# stan-docker

## Table of Contents  

* [Introduction](#introduction) 

* [Stan](#stan) 

* [Docker](#docker) 

### Introduction

A Docker image to run Stan, rstanarm, and brms for Bayesian statistical modelling

Launch an RStudio webserver using `bash stan_serve.sh`.

Execute `docker pull ghcr.io/jbris/stan-docker:latest` or `bash docker_pull.sh` to pull the image.

To convert the image into a Singularity container, run `singularity pull docker://ghcr.io/jbris/stan-docker:latest` or `bash singularity_pull.sh`.

### Stan

The following packages are installed during the image build process:

* [Stan](https://mc-stan.org/)

* [RStan](https://mc-stan.org/users/interfaces/rstan)

* [rstanarm](https://mc-stan.org/rstanarm/)

* [brms](https://paul-buerkner.github.io/brms/)

* [tidybayes](https://mjskay.github.io/tidybayes/)

* [bayesplot](https://mc-stan.org/bayesplot/)

### Docker

This Docker image extends from `rocker/tidyverse`. [Click this link for more information about the Rocker project.](https://rocker-project.org/images/)

Running the Docker container will launch an RStudio web server. You can access RStudio by visiting localhost:$R_STUDIO_PORT on your web browser. See [.env](.env) for the defined environment variables.

Running docker-compose will bind a volume, mapping the container's `home` directory to a local `r_home` directory.

See the [Dockerfile](Dockerfile) for the instructions executed during the build of the Docker image. 

View [docker-compose.yaml](docker-compose.yaml) to see the definition for the Stan service.