jgabry / Bayes Vis Paper
'Visualization in Bayesian workflow' by Gabry, Simpson, Vehtari, Betancourt, and Gelman. (JRSS discussion paper and code)
Stars: ✭ 47
Programming Languages
r
7636 projects
Projects that are alternatives of or similar to Bayes Vis Paper
Loo
loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)
Stars: ✭ 106 (+125.53%)
Mutual labels: bayesian-data-analysis, stan
Bda py demos
Bayesian Data Analysis demos for Python
Stars: ✭ 781 (+1561.7%)
Mutual labels: bayesian-data-analysis, stan
Bda r demos
Bayesian Data Analysis demos for R
Stars: ✭ 409 (+770.21%)
Mutual labels: bayesian-data-analysis, stan
Tidybayes
Bayesian analysis + tidy data + geoms (R package)
Stars: ✭ 557 (+1085.11%)
Mutual labels: bayesian-data-analysis, stan
Stan
Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Stars: ✭ 2,177 (+4531.91%)
Mutual labels: bayesian-data-analysis, stan
Shinystan
shinystan R package and ShinyStan GUI
Stars: ✭ 172 (+265.96%)
Mutual labels: bayesian-data-analysis, stan
Ggmcmc
Graphical tools for analyzing Markov Chain Monte Carlo simulations from Bayesian inference
Stars: ✭ 95 (+102.13%)
Mutual labels: bayesian-data-analysis, stan
Rstan
RStan, the R interface to Stan
Stars: ✭ 760 (+1517.02%)
Mutual labels: bayesian-data-analysis, stan
Rstanarm
rstanarm R package for Bayesian applied regression modeling
Stars: ✭ 285 (+506.38%)
Mutual labels: bayesian-data-analysis, stan
Bayesian Stats Modelling Tutorial
How to do Bayesian statistical modelling using numpy and PyMC3
Stars: ✭ 480 (+921.28%)
Mutual labels: bayesian-data-analysis
Math
The Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic modeling, linear algebra, and equation solving.
Stars: ✭ 494 (+951.06%)
Mutual labels: stan
Rhat ess
Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC
Stars: ✭ 19 (-59.57%)
Mutual labels: bayesian-data-analysis
Covid19model
Code for modelling estimated deaths and cases for COVID19.
Stars: ✭ 913 (+1842.55%)
Mutual labels: stan
Brms
brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
Stars: ✭ 825 (+1655.32%)
Mutual labels: stan
Bayesian Analysis Recipes
A collection of Bayesian data analysis recipes using PyMC3
Stars: ✭ 479 (+919.15%)
Mutual labels: bayesian-data-analysis
Orbit
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Stars: ✭ 346 (+636.17%)
Mutual labels: stan
Gpmicrobiome
A novel probabilistic approach to explicitly model overdispersion and sampling zeros in 16S rRNA sequencing data by considering the temporal correlation between nearby time points using Gaussian Processes
Stars: ✭ 5 (-89.36%)
Mutual labels: stan
Bayadera
High-performance Bayesian Data Analysis on the GPU in Clojure
Stars: ✭ 342 (+627.66%)
Mutual labels: bayesian-data-analysis
Visualization in Bayesian workflow
This repository contains all materials for 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
- Published JRSS version: https://rss.onlinelibrary.wiley.com/doi/full/10.1111/rssa.12378
- arXiv preprint: https://arxiv.org/pdf/1709.01449.pdf (includes Supplementary Materials in appendix)
- bayesplot R package: https://mc-stan.org/bayesplot, https://github.com/stan-dev/bayesplot
Repository contents
-
bayes-vis.pdf: Latest draft of the paper as PDF. -
bayes-vis.tex: Main tex file for the paper. -
bayes-vis.R: R code for fitting the models and making plots. -
bayes-vis.RData: Contains data needed inbayes-vis.R. -
maps.R: R code for making maps. -
standirectory: Contains Stan programs needed inbayes-vis.R.
Note that the project description data, including the texts, logos, images, and/or trademarks,
for each open source project belongs to its rightful owner.
If you wish to add or remove any projects, please contact us at [email protected].