rstan - R Interface to Stan
User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.
Last updated 15 hours ago
bayesian-data-analysisbayesian-inferencebayesian-statisticsmcmcstancpp
18.53 score 1.1k stars 277 dependents 14k scripts 57k downloads
loo - Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models
Efficient approximate leave-one-out cross-validation (LOO) for Bayesian models fit using Markov chain Monte Carlo, as described in Vehtari, Gelman, and Gabry (2017) <doi:10.1007/s11222-016-9696-4>. The approximation uses Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct of the calculations, we also obtain approximate standard errors for estimated predictive errors and for the comparison of predictive errors between models. The package also provides methods for using stacking and other model weighting techniques to average Bayesian predictive distributions.
Last updated 22 days ago
bayesbayesianbayesian-data-analysisbayesian-inferencebayesian-methodsbayesian-statisticscross-validationinformation-criterionmodel-comparisonstan
17.32 score 151 stars 290 dependents 2.6k scripts 47k downloads
bayesplot - Plotting for Bayesian Models
Plotting functions for posterior analysis, MCMC diagnostics, prior and posterior predictive checks, and other visualizations to support the applied Bayesian workflow advocated in Gabry, Simpson, Vehtari, Betancourt, and Gelman (2019) <doi:10.1111/rssa.12378>. The package is designed not only to provide convenient functionality for users, but also a common set of functions that can be easily used by developers working on a variety of R packages for Bayesian modeling, particularly (but not exclusively) packages interfacing with 'Stan'.
Last updated 1 months ago
bayesianggplot2mcmcpandocstanstatistical-graphicsvisualization
16.69 score 436 stars 98 dependents 6.5k scripts 30k downloads
posterior - Tools for Working with Posterior Distributions
Provides useful tools for both users and developers of packages for fitting Bayesian models or working with output from Bayesian models. The primary goals of the package are to: (a) Efficiently convert between many different useful formats of draws (samples) from posterior or prior distributions. (b) Provide consistent methods for operations commonly performed on draws, for example, subsetting, binding, or mutating draws. (c) Provide various summaries of draws in convenient formats. (d) Provide lightweight implementations of state of the art posterior inference diagnostics. References: Vehtari et al. (2021) <doi:10.1214/20-BA1221>.
Last updated 3 days ago
bayesbayesianmcmc
16.13 score 168 stars 342 dependents 3.3k scripts 56k downloads
rstanarm - Bayesian Applied Regression Modeling via Stan
Estimates previously compiled regression models using the 'rstan' package, which provides the R interface to the Stan C++ library for Bayesian estimation. Users specify models via the customary R syntax with a formula and data.frame plus some additional arguments for priors.
Last updated 9 months ago
bayesianbayesian-data-analysisbayesian-inferencebayesian-methodsbayesian-statisticsmultilevel-modelsrstanrstanarmstanstatistical-modelingcpp
15.65 score 393 stars 12 dependents 5.0k scripts 13k downloadsStanHeaders - C++ Header Files for Stan
The C++ header files of the Stan project are provided by this package, but it contains little R code or documentation. The main reference is the vignette. There is a shared object containing part of the 'CVODES' library, but its functionality is not accessible from R. 'StanHeaders' is primarily useful for developers who want to utilize the 'LinkingTo' directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies. The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or 'variational' methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, 'templated' statistical and linear algebra functions that can handle the automatically 'differentiable' scalar types (and doubles, 'ints', etc.), and a parser for the Stan language. The 'rstan' package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models.
Last updated 15 hours ago
bayesian-data-analysisbayesian-inferencebayesian-statisticsmcmcstan
15.41 score 1.1k stars 342 dependents 291 scripts 66k downloads
rstantools - Tools for Developing R Packages Interfacing with 'Stan'
Provides various tools for developers of R packages interfacing with 'Stan' <https://mc-stan.org>, including functions to set up the required package structure, S3 generics and default methods to unify function naming across 'Stan'-based R packages, and vignettes with recommendations for developers.
Last updated 1 months ago
bayesian-data-analysisbayesian-statisticsdeveloper-toolsstan
13.09 score 50 stars 222 dependents 134 scripts 43k downloads
shinystan - Interactive Visual and Numerical Diagnostics and Posterior Analysis for Bayesian Models
A graphical user interface for interactive Markov chain Monte Carlo (MCMC) diagnostics and plots and tables helpful for analyzing a posterior sample. The interface is powered by the 'Shiny' web application framework from 'RStudio' and works with the output of MCMC programs written in any programming language (and has extended functionality for 'Stan' models fit using the 'rstan' and 'rstanarm' packages).
Last updated 3 years ago
bayesianbayesian-data-analysisbayesian-inferencebayesian-methodsbayesian-statisticsmcmcshiny-appsstanstatistical-graphics
13.05 score 198 stars 13 dependents 1.6k scripts 13k downloads
cmdstanr - R Interface to 'CmdStan'
A lightweight interface to 'Stan' <https://mc-stan.org>. The 'CmdStanR' interface is an alternative to 'RStan' that calls the command line interface for compilation and running algorithms instead of interfacing with C++ via 'Rcpp'. This has many benefits including always being compatible with the latest version of Stan, fewer installation errors, fewer unexpected crashes in RStudio, and a more permissive license.
Last updated 9 months ago
bayesbayesianmarkov-chain-monte-carlomaximum-likelihoodmcmcstanvariational-inference
12.27 score 145 stars 9 dependents 5.2k scripts
projpred - Projection Predictive Feature Selection
Performs projection predictive feature selection for generalized linear models (Piironen, Paasiniemi, and Vehtari, 2020, <doi:10.1214/20-EJS1711>) with or without multilevel or additive terms (Catalina, Bürkner, and Vehtari, 2022, <https://proceedings.mlr.press/v151/catalina22a.html>), for some ordinal and nominal regression models (Weber, Glass, and Vehtari, 2023, <arXiv:2301.01660>), and for many other regression models (using the latent projection by Catalina, Bürkner, and Vehtari, 2021, <arXiv:2109.04702>, which can also be applied to most of the former models). The package is compatible with the 'rstanarm' and 'brms' packages, but other reference models can also be used. See the vignettes and the documentation for more information and examples.
Last updated 25 days ago
bayesbayesianbayesian-inferencerstanarmstanstatisticsvariable-selectionopenblascpp
10.05 score 111 stars 241 scripts 1.7k downloadsposteriordb - R functionality for posteriordb
R functionality of easy handling of the posteriordb posteriors.
Last updated 1 years ago
3.37 score 8 stars 59 scripts