R package citation, R package reverse dependencies, R package scholars, install an r package from GitHub hy is package acceptance pending why is package undeliverable amazon why is package on hold dhl tour packages why in r package r and r package full form why is r free why r is bad which r package to install which r package has which r package which r package version which r package readxl which r package ggplot which r package fread which r package license where is package.json where is package-lock.json where is package.swift where is package explorer in eclipse where is package where is package manager unity where is package installer android where is package manager console in visual studio who r package which r package to install which r package version who is package who is package deal who is package design r and r package full form r and r package meaning what r package has what package r what is package in java what is package what is package-lock.json what is package in python what is package.json what is package installer do r package can't install r packages r can't find package r can't load package can't load xlsx package r can't install psych package r can't install sf package r Write if else in NONMEM pk pd
brms
Bayesian Regression Models using 'Stan'
View on CRAN: Click
here
Download and install brms package within the R console
Install from CRAN:
install.packages("brms")
Install from Github:
library("remotes")
install_github("cran/brms") Install by package version:
library("remotes")
install_version("brms", "2.23.0") Attach the package and use:
library("brms")
Maintained by
Paul-Christian Bürkner
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-05-08
Latest Update: 2024-09-23
Description:
Fit Bayesian generalized (non-)linear multivariate multilevel models
using 'Stan' for full Bayesian inference. A wide range of distributions
and link functions are supported, allowing users to fit -- among others --
linear, robust linear, count data, survival, response times, ordinal,
zero-inflated, hurdle, and even self-defined mixture models all in a
multilevel context. Further modeling options include both theory-driven and
data-driven non-linear terms, auto-correlation structures, censoring and
truncation, meta-analytic standard errors, and quite a few more.
In addition, all parameters of the response distribution can be predicted
in order to perform distributional regression. Prior specifications are
flexible and explicitly encourage users to apply prior distributions that
actually reflect their prior knowledge. Models can easily be evaluated and
compared using several methods assessing posterior or prior predictions.
References: B
How to cite:
Paul-Christian Bürkner (2015). brms: Bayesian Regression Models using 'Stan'. R package version 2.23.0, https://cran.r-project.org/web/packages/brms. Accessed 08 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:23), 0.1.0 (2015-05-08 11:47), 0.2.0 (2015-05-27 01:35), 0.3.0 (2015-06-29 16:41), 0.4.0 (2015-07-23 15:24), 0.4.1 (2015-08-03 00:20), 0.5.0 (2015-09-13 09:22), 0.6.0 (2015-11-14 00:06), 0.7.0 (2016-01-18 13:17), 0.8.0 (2016-02-15 23:59), 0.9.0 (2016-04-19 13:50), 0.9.1 (2016-05-17 21:13), 0.10.0 (2016-06-29 17:03), 1.0.0 (2016-09-15 03:00), 1.0.1 (2016-09-16 12:50), 1.1.0 (2016-10-11 23:53), 1.2.0 (2016-12-06 11:28), 1.3.0 (2016-12-20 00:55), 1.3.1 (2016-12-22 00:38), 1.4.0 (2017-01-27 18:47), 1.5.0 (2017-02-17 19:02), 1.5.1 (2017-02-26 19:56), 1.6.0 (2017-04-06 23:05), 1.6.1 (2017-04-17 15:54), 1.7.0 (2017-05-23 19:29), 1.8.0 (2017-07-20 21:53), 1.9.0 (2017-08-15 14:18), 1.10.0 (2017-09-09 23:51), 1.10.2 (2017-10-20 22:52), 2.0.0 (2017-12-15 13:58), 2.0.1 (2017-12-21 22:24), 2.1.0 (2018-01-23 22:48), 2.2.0 (2018-04-13 10:43), 2.3.0 (2018-05-14 17:47), 2.3.1 (2018-06-05 19:43), 2.4.0 (2018-07-20 23:50), 2.5.0 (2018-09-16 18:40), 2.6.0 (2018-10-23 12:40), 2.7.0 (2018-12-17 17:00), 2.8.0 (2019-03-15 10:13), 2.9.0 (2019-05-23 07:00), 2.10.0 (2019-08-29 17:50), 2.11.0 (2020-01-12 15:50), 2.11.1 (2020-01-19 21:00), 2.12.0 (2020-02-23 18:30), 2.13.0 (2020-05-27 07:30), 2.13.3 (2020-07-13 15:10), 2.13.5 (2020-07-31 10:40), 2.14.0 (2020-10-08 16:20), 2.14.4 (2020-11-03 07:40), 2.15.0 (2021-03-14 16:50), 2.16.0 (2021-08-19 00:00), 2.16.1 (2021-08-23 16:00), 2.16.3 (2021-11-22 20:50), 2.17.0 (2022-04-13 16:22), 2.18.0 (2022-09-19 15:56), 2.19.0 (2023-03-14 16:40), 2.20.1 (2023-08-14 09:10), 2.20.3 (2023-09-15 19:12), 2.20.4 (2023-09-25 21:00), 2.21.0 (2024-03-20 13:30), 2.22.0 (2024-09-23 15:01)
Other packages that cited brms R package
View brms citation profile
Other R packages that brms depends,
imports, suggests or enhances
Complete documentation for brms
Functions, R codes and Examples using
the brms R package
Some associated functions: AsymLaplace . BetaBinomial . Dirichlet . ExGaussian . Frechet . GenExtremeValue . Hurdle . InvGaussian . LogisticNormal . MultiNormal . MultiStudentT . R2D2 . Shifted_Lognormal . SkewNormal . StudentT . VarCorr.brmsfit . VonMises . Wiener . ZeroInflated . add_criterion . add_ic . add_rstan_model . addition-terms . ar . arma . as.brmsprior . as.data.frame.brmsfit . as.mcmc.brmsfit . autocor-terms . autocor.brmsfit . bayes_R2.brmsfit . bayes_factor.brmsfit . bridge_sampler.brmsfit . brm . brm_multiple . brms-package . brmsfamily . brmsfit-class . brmsfit_needs_refit . brmsformula-helpers . brmsformula . brmshypothesis . brmsterms . car . coef.brmsfit . combine_models . compare_ic . conditional_effects.brmsfit . conditional_smooths.brmsfit . control_params . cor_ar . cor_arma . cor_arr . cor_brms . cor_bsts . cor_car . cor_cosy . cor_fixed . cor_ma . cor_sar . cosy . cs . custom_family . data_predictor . data_response . density_ratio . diagnostic-quantities . do_call . draws-brms . draws-index-brms . emmeans-brms-helpers . epilepsy . expose_functions.brmsfit . expp1 . family.brmsfit . fcor . fitted.brmsfit . fixef.brmsfit . get_dpar . get_prior . get_refmodel.brmsfit . get_y . gp . gr . horseshoe . hypothesis.brmsfit . inhaler . inv_logit_scaled . is.brmsfit . is.brmsfit_multiple . is.brmsformula . is.brmsprior . is.brmsterms . is.cor_brms . is.mvbrmsformula . is.mvbrmsterms . kfold.brmsfit . kfold_predict . kidney . lasso . launch_shinystan.brmsfit . log_lik.brmsfit . logit_scaled . logm1 . loo.brmsfit . loo_R2.brmsfit . loo_compare.brmsfit . loo_model_weights.brmsfit . loo_moment_match.brmsfit . loo_predict.brmsfit . loo_subsample.brmsfit . loss . ma . make_conditions . make_stancode . make_standata . mcmc_plot.brmsfit . me . mi . mixture . mm . mmc . mo . model_weights.brmsfit . mvbind . mvbrmsformula . ngrps.brmsfit . nsamples.brmsfit . opencl . pairs.brmsfit . parnames . plot.brmsfit . post_prob.brmsfit . posterior_average.brmsfit . posterior_epred.brmsfit . posterior_interval.brmsfit . posterior_linpred.brmsfit . posterior_predict.brmsfit . posterior_samples.brmsfit . posterior_smooths.brmsfit . posterior_summary . posterior_table . pp_average.brmsfit . pp_check.brmsfit . pp_mixture.brmsfit . predict.brmsfit . predictive_error.brmsfit . predictive_interval.brmsfit . prepare_predictions . print.brmsfit . print.brmsprior . prior_draws.brmsfit . prior_summary.brmsfit . ranef.brmsfit . recompile_model . reloo.brmsfit . rename_pars . residuals.brmsfit . restructure . rows2labels . s . sar . save_pars . set_prior . stancode.brmsfit . standata.brmsfit . stanvar . summary.brmsfit . theme_black . theme_default . threading . unstr . update.brmsfit . update.brmsfit_multiple . update_adterms . validate_newdata . validate_prior . vcov.brmsfit . waic.brmsfit .
Some associated R codes: autocor.R . backends.R . bayes_R2.R . bridgesampling.R . brm.R . brm_multiple.R . brms-package.R . brmsfit-class.R . brmsfit-helpers.R . brmsfit-methods.R . brmsformula.R . brmsterms.R . conditional_effects.R . conditional_smooths.R . data-helpers.R . data-predictor.R . data-response.R . datasets.R . diagnostics.R . distributions.R . emmeans.R . exclude_pars.R . exclude_terms.R . families.R . family-lists.R . formula-ac.R . formula-ad.R . formula-cs.R . formula-gp.R . formula-re.R . formula-sm.R . formula-sp.R . ggplot-themes.R . hypothesis.R . kfold.R . launch_shinystan.R . log_lik.R . loo.R . loo_moment_match.R . loo_predict.R . loo_subsample.R . lsp.R . make_stancode.R . make_standata.R . misc.R . model_weights.R . numeric-helpers.R . plot.R . posterior.R . posterior_epred.R . posterior_predict.R . posterior_samples.R . posterior_smooths.R . pp_check.R . pp_mixture.R . predictive_error.R . predictor.R . prepare_predictions.R . prior_draws.R . priors.R . projpred.R . reloo.R . rename_pars.R . restructure.R . stan-helpers.R . stan-likelihood.R . stan-predictor.R . stan-prior.R . stan-response.R . stanvars.R . summary.R . update.R . zzz.R . Full brms package functions and examples
Downloads during the last 30 days
Today's Hot Picks in Authors and Packages
nextGenShinyApps
Craft Exceptional 'R Shiny' Applications and Dashboards with Novel Responsive Tools
Nove responsive tools for designing and developing 'Shiny' dashboards and applications. The scripts ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Obinna Obianom (view profile)
shinymodels
Interactive Assessments of Models
Launch a 'shiny' application for 'tidymodels' results. For
classification or regression models, the ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Simon Couch (view profile)
kriens
Continuation Passing Style Development
Provides basic functions for Continuation-Passing Style development. ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Matteo Provenzano (view profile)
imguR
An Imgur.com API Client Package
A complete API client for the image hosting service Imgur.com, including the an imgur graphics devic ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Thomas J. Leeper (view profile)
eDMA
Dynamic Model Averaging with Grid Search
Perform dynamic model averaging with grid search as in Dangl and Halling (2012) ...
Download / Learn more Package Citations See dependency
Download / Learn more Package Citations See dependency
Maintainer: Leopoldo Catania (view profile)
28,989
R Packages
247,686
Dependencies
76,495
Author Associations
28,990
Publication Badges
