Skip to content

mitzimorris/StanCon2023_brms_tutorial

Repository files navigation

Notebooks and data for StanCon 2023 Tutorial on BRMS

This tutorial works through the example dataset from the paper Visualization in Bayesian workflow:

Gabry, J. , Simpson, D. , Vehtari, A. , Betancourt, M. and Gelman, A. (2019),
Visualization in Bayesian workflow. J. R. Stat. Soc. A, 182: 389-402. doi:10.1111/rssa.12378

Exploratory Data Analysis

Notebooks "eda_air" are visualizations of the dataset in subdirectory data.

This dataset is GIS data, which requires either

Fitting Models in BRMS

Notebooks "fit_air_brms" use BRMS to specify and fit the 3 models from the paper. To run these notebooks you must install the R packages BRMS and cmdstanr. The input data is in JSON format, and therefore doesn't require the sf library.

About

Notebooks and data for StanCon2023 tutorial on BRMS

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published