AsymLaplace             The Asymmetric Laplace Distribution
ExGaussian              The Exponentially Modified Gaussian
                        Distribution
Frechet                 The Frechet Distribution
GenExtremeValue         The Generalized Extreme Value Distribution
Hurdle                  Hurdle Distributions
InvGaussian             The Inverse Gaussian Distribution
MultiNormal             The Multivariate Normal Distribution
MultiStudentT           The Multivariate Student-t Distribution
Shifted_Lognormal       The Shifted Log Normal Distribution
SkewNormal              The Skew-Normal Distribution
StudentT                The Student-t Distribution
VarCorr.brmsfit         Extract Variance and Correlation Components
VonMises                The von Mises Distribution
Wiener                  The Wiener Diffusion Model Distribution
ZeroInflated            Zero-Inflated Distributions
add_ic                  Add information criteria and fit indices to
                        fitted model objects
addition-terms          Additional Response Information
as.mcmc.brmsfit         Extract posterior samples for use with the
                        'coda' package
autocor                 Extract Autocorrelation Structures
bayes_R2.brmsfit        Compute a Bayesian version of R-squared for
                        regression models
bayes_factor.brmsfit    Bayes Factors from Marginal Likelihoods
bridge_sampler.brmsfit
                        Log Marginal Likelihood via Bridge Sampling
brm                     Fit Bayesian Generalized (Non-)Linear
                        Multivariate Multilevel Models
brm_multiple            Run the same 'brms' model on multiple datasets
brms-package            Bayesian Regression Models using 'Stan'
brmsfamily              Special Family Functions for 'brms' Models
brmsfit-class           Class 'brmsfit' of models fitted with the
                        'brms' package
brmsformula             Set up a model formula for use in 'brms'
brmsformula-helpers     Linear and Non-linear formulas in 'brms'
brmshypothesis          Descriptions of 'brmshypothesis' Objects
coef.brmsfit            Extract Model Coefficients
combine_models          Combine Models fitted with 'brms'
compare_ic              Compare Information Criteria of Different
                        Models
control_params.brmsfit
                        Extract Control Parameters of the NUTS Sampler
cor_ar                  AR(p) correlation structure
cor_arma                ARMA(p,q) correlation structure
cor_arr                 ARR(r) correlation structure
cor_brms                Correlation structure classes for the 'brms'
                        package
cor_bsts                Basic Bayesian Structural Time Series
cor_car                 Spatial conditional autoregressive (CAR)
                        structures
cor_fixed               Fixed user-defined covariance matrices
cor_ma                  MA(q) correlation structure
cor_sar                 Spatial simultaneous autoregressive (SAR)
                        structures
cs                      Category Specific Predictors in 'brms' Models
custom_family           Custom Families in 'brms' Models
density_ratio           Compute Density Ratios
epilepsy                Epileptic seizure counts
expose_functions.brmsfit
                        Expose user-defined 'Stan' functions
expp1                   Exponential function plus one.
extract_draws.brmsfit   Extract Data and Posterior Draws
fitted.brmsfit          Extract Model Fitted Values of 'brmsfit'
                        Objects
fixef.brmsfit           Extract Population-Level Estimates
get_prior               Overview on Priors for 'brms' Models
gp                      Set up Gaussian process terms in 'brms'
gr                      Set up basic grouping terms in 'brms'
horseshoe               Set up a horseshoe prior in 'brms'
hypothesis.brmsfit      Non-Linear Hypothesis Testing
inhaler                 Clarity of inhaler instructions
inv_logit_scaled        Scaled inverse logit-link
is.brmsfit              Checks if argument is a 'brmsfit' object
is.brmsfit_multiple     Checks if argument is a 'brmsfit_multiple'
                        object
is.brmsformula          Checks if argument is a 'brmsformula' object
is.brmsprior            Checks if argument is a 'brmsprior' object
is.brmsterms            Checks if argument is a 'brmsterms' object
is.cor_brms             Check if argument is a correlation structure
is.mvbrmsformula        Checks if argument is a 'mvbrmsformula' object
is.mvbrmsterms          Checks if argument is a 'mvbrmsterms' object
kfold.brmsfit           K-Fold Cross-Validation
kidney                  Infections in kidney patients
lasso                   Set up a lasso prior in 'brms'
launch_shinystan.brmsfit
                        Interface to 'shinystan'
log_lik.brmsfit         Compute the Pointwise Log-Likelihood
log_posterior.brmsfit   Extract Diagnostic Quantities of 'brms' Models
logit_scaled            Scaled logit-link
logm1                   Logarithm with a minus one offset.
loo.brmsfit             Compute the LOO information criterion
loo_R2.brmsfit          Compute a LOO-adjusted R-squared for regression
                        models
loo_model_weights.brmsfit
                        Model averaging via stacking or pseudo-BMA
                        weighting.
loo_predict.brmsfit     Compute Weighted Expectations Using LOO
make_conditions         Prepare Fully Crossed Conditions
make_stancode           Stan Code for 'brms' Models
make_standata           Data for 'brms' Models
marginal_effects.brmsfit
                        Display Marginal Effects of Predictors
marginal_smooths.brmsfit
                        Display Smooth Terms
me                      Predictors with Measurement Error in 'brms'
                        Models
mi                      Predictors with Missing Values in 'brms' Models
mixture                 Finite Mixture Families in 'brms'
mm                      Set up multi-membership grouping terms in
                        'brms'
mmc                     Multi-Membership Covariates
mo                      Monotonic Predictors in 'brms' Models
model_weights.brmsfit   Model Weighting Methods
mvbrmsformula           Set up a multivariate model formula for use in
                        'brms'
ngrps.brmsfit           Number of levels
nsamples.brmsfit        Number of Posterior Samples
pairs.brmsfit           Create a matrix of output plots from a
                        'brmsfit' object
parnames                Extract Parameter Names
parse_bf                Parse Formulas of 'brms' Models
plot.brmsfit            Trace and Density Plots for MCMC Samples
post_prob.brmsfit       Posterior Model Probabilities from Marginal
                        Likelihoods
posterior_average.brmsfit
                        Posterior samples of parameters averaged across
                        models
posterior_interval.brmsfit
                        Compute posterior uncertainty intervals
posterior_samples.brmsfit
                        Extract posterior samples
posterior_summary.brmsfit
                        Summarize Posterior Samples
posterior_table         Table Creation for Posterior Samples
pp_average.brmsfit      Posterior predictive samples averaged across
                        models
pp_check.brmsfit        Posterior Predictive Checks for 'brmsfit'
                        Objects
pp_mixture.brmsfit      Posterior Probabilities of Mixture Component
                        Memberships
predict.brmsfit         Model Predictions of 'brmsfit' Objects
predictive_interval.brmsfit
                        Predictive Intervals
print.brmsfit           Print a summary for a fitted model represented
                        by a 'brmsfit' object
print.brmsprior         Print method for 'brmsprior' objects
prior_samples.brmsfit   Extract prior samples
prior_summary.brmsfit   Extract Priors of a Bayesian Model Fitted with
                        'brms'
ranef.brmsfit           Extract Group-Level Estimates
reloo                   Compute exact cross-validation for problematic
                        observations
residuals.brmsfit       Extract Model Residuals from brmsfit Objects
restructure             Restructure Old 'brmsfit' Objects
rows2labels             Convert Rows to Labels
s                       Defining smooths in 'brms' formulas
set_prior               Prior Definitions for 'brms' Models
stancode.brmsfit        Extract Stan model code
standata.brmsfit        Extract Data passed to Stan
stanplot.brmsfit        MCMC Plots Implemented in 'bayesplot'
stanvar                 User-defined variables passed to Stan
summary.brmsfit         Create a summary of a fitted model represented
                        by a 'brmsfit' object
theme_black             Black Theme for 'ggplot2' Graphics
theme_default           Default 'bayesplot' Theme for 'ggplot2'
                        Graphics
update.brmsfit          Update 'brms' models
update_adterms          Update Formula Addition Terms
validate_newdata        Validate New Data
vcov.brmsfit            Covariance and Correlation Matrix of
                        Population-Level Effects
waic.brmsfit            Compute the WAIC
