rstanarm

Bayesian Applied Regression Modeling via Stan

Last update: 18 January 2024

Copyright license: GNU General Public License

Software version identifier: 2.21.4, 2.9.0-1, 2.9.0-3, 2.9.0-4, 2.10.1, 2.11.1, 2.12.1, 2.13.1, 2.14.1, 2.15.2, 2.15.3, 2.17.2, 2.17.3, 2.17.4, 2.18.1, 2.18.2, 2.19.2, 2.19.3, 2.21.1, 2.21.3, 2.26.1, 2.32.1

Source code repository: https://github.com/cran/rstanarm

Description

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.

Related Items (21)

Quantifying conditional probability tables in Bayesian networks: Bayesian regression for scenario-based encoding of elicited expert assessments on feral pig habitat ⋮ A comparative study on the performance of frequentist and Bayesian estimation methods under separation in logistic regression ⋮ Optimal group decision: a matter of confidence calibration ⋮ Projective inference in high-dimensional problems: prediction and feature selection ⋮ Bayes Rules! ⋮ Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC ⋮ Simultaneous transformation and rounding (STAR) models for integer-valued data ⋮ webSDM ⋮ IRexamples ⋮ tidyposterior ⋮ Active matrix factorization for surveys ⋮ evidence ⋮ eefAnalytics ⋮ fbst ⋮ BayesPostEst ⋮ R kompakt ⋮ Shrinkage priors for Bayesian penalized regression ⋮ jmBIG ⋮ Enriching Students’ Conceptual Understanding of Confidence Intervals: An Interactive Trivia-Based Classroom Activity ⋮ bayesrules ⋮ Rank-normalization, folding, and localization: an improved \(\widehat{R}\) for assessing convergence of MCMC (with Discussion)

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