Bayesian Regression Models using 'Stan'

Documentation for package ‘brms’ version 2.19.0

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Bayesian Regression Models using 'Stan'

-- A --

acat	Special Family Functions for 'brms' Models
acformula	Linear and Non-linear formulas in 'brms'
addition-terms	Additional Response Information
add_criterion	Add model fit criteria to model objects
add_criterion.brmsfit	Add model fit criteria to model objects
add_ic	Add model fit criteria to model objects
add_ic.brmsfit	Add model fit criteria to model objects
add_ic<-	Add model fit criteria to model objects
add_loo	Add model fit criteria to model objects
add_rstan_model	Add compiled 'rstan' models to 'brmsfit' objects
add_waic	Add model fit criteria to model objects
and	Index 'brmsfit' objects
ar	Set up AR(p) correlation structures
arma	Set up ARMA(p,q) correlation structures
as.array.brmsfit	Extract Posterior Draws
as.data.frame.brmsfit	Extract Posterior Draws
as.matrix.brmsfit	Extract Posterior Draws
as.mcmc	Extract posterior samples for use with the 'coda' package
as.mcmc.brmsfit	Extract posterior samples for use with the 'coda' package
AsymLaplace	The Asymmetric Laplace Distribution
asym_laplace	Special Family Functions for 'brms' Models
as_draws	Transform 'brmsfit' to 'draws' objects
as_draws.brmsfit	Transform 'brmsfit' to 'draws' objects
as_draws_array	Transform 'brmsfit' to 'draws' objects
as_draws_array.brmsfit	Transform 'brmsfit' to 'draws' objects
as_draws_df	Transform 'brmsfit' to 'draws' objects
as_draws_df.brmsfit	Transform 'brmsfit' to 'draws' objects
as_draws_list	Transform 'brmsfit' to 'draws' objects
as_draws_list.brmsfit	Transform 'brmsfit' to 'draws' objects
as_draws_matrix	Transform 'brmsfit' to 'draws' objects
as_draws_matrix.brmsfit	Transform 'brmsfit' to 'draws' objects
as_draws_rvars	Transform 'brmsfit' to 'draws' objects
as_draws_rvars.brmsfit	Transform 'brmsfit' to 'draws' objects
autocor	(Deprecated) Extract Autocorrelation Objects
autocor-terms	Autocorrelation structures
autocor.brmsfit	(Deprecated) Extract Autocorrelation Objects

-- B --

bayes_factor	Bayes Factors from Marginal Likelihoods
bayes_factor.brmsfit	Bayes Factors from Marginal Likelihoods
bayes_R2	Compute a Bayesian version of R-squared for regression models
bayes_R2.brmsfit	Compute a Bayesian version of R-squared for regression models
bernoulli	Special Family Functions for 'brms' Models
Beta	Special Family Functions for 'brms' Models
BetaBinomial	The Beta-binomial Distribution
beta_binomial	Special Family Functions for 'brms' Models
bf	Set up a model formula for use in 'brms'
bf-helpers	Linear and Non-linear formulas in 'brms'
bridge_sampler	Log Marginal Likelihood via Bridge Sampling
bridge_sampler.brmsfit	Log Marginal Likelihood via Bridge Sampling
brm	Fit Bayesian Generalized (Non-)Linear Multivariate Multilevel Models
brms	Bayesian Regression Models using 'Stan'
brmsfamily	Special Family Functions for 'brms' Models
brmsfit	Class 'brmsfit' of models fitted with the 'brms' package
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
brmsprior	Prior Definitions for 'brms' Models
brmsprior-class	Prior Definitions for 'brms' Models
brmsterms	Parse Formulas of 'brms' Models
brmsterms.brmsformula	Parse Formulas of 'brms' Models
brmsterms.default	Parse Formulas of 'brms' Models
brmsterms.mvbrmsformula	Parse Formulas of 'brms' Models
brm_multiple	Run the same 'brms' model on multiple datasets

-- C --

car	Spatial conditional autoregressive (CAR) structures
cat	Additional Response Information
categorical	Special Family Functions for 'brms' Models
cens	Additional Response Information
chains,	Index 'brmsfit' objects
coef.brmsfit	Extract Model Coefficients
combine_models	Combine Models fitted with 'brms'
compare_ic	Compare Information Criteria of Different Models
conditional_effects	Display Conditional Effects of Predictors
conditional_effects.brmsfit	Display Conditional Effects of Predictors
conditional_smooths	Display Smooth Terms
conditional_smooths.brmsfit	Display Smooth Terms
control_params	Extract Control Parameters of the NUTS Sampler
control_params.brmsfit	Extract Control Parameters of the NUTS Sampler
cor_ar	(Deprecated) AR(p) correlation structure
cor_arma	(Deprecated) ARMA(p,q) correlation structure
cor_arma-class	(Deprecated) ARMA(p,q) correlation structure
cor_brms	(Deprecated) Correlation structure classes for the 'brms' package
cor_brms-class	(Deprecated) Correlation structure classes for the 'brms' package
cor_car	(Deprecated) Spatial conditional autoregressive (CAR) structures
cor_cosy	(Deprecated) Compound Symmetry (COSY) Correlation Structure
cor_cosy-class	(Deprecated) Compound Symmetry (COSY) Correlation Structure
cor_errorsar	(Deprecated) Spatial simultaneous autoregressive (SAR) structures
cor_fixed	(Deprecated) Fixed user-defined covariance matrices
cor_icar	(Deprecated) Spatial conditional autoregressive (CAR) structures
cor_lagsar	(Deprecated) Spatial simultaneous autoregressive (SAR) structures
cor_ma	(Deprecated) MA(q) correlation structure
cor_sar	(Deprecated) Spatial simultaneous autoregressive (SAR) structures
cosy	Set up COSY correlation structures
cov_fixed	(Deprecated) Fixed user-defined covariance matrices
cox	Special Family Functions for 'brms' Models
cratio	Special Family Functions for 'brms' Models
cs	Category Specific Predictors in 'brms' Models
cse	Category Specific Predictors in 'brms' Models
cumulative	Special Family Functions for 'brms' Models
customfamily	Custom Families in 'brms' Models
custom_family	Custom Families in 'brms' Models

-- D --

dasym_laplace	The Asymmetric Laplace Distribution
dbeta_binomial	The Beta-binomial Distribution
ddirichlet	The Dirichlet Distribution
dec	Additional Response Information
density_ratio	Compute Density Ratios
dexgaussian	The Exponentially Modified Gaussian Distribution
dfrechet	The Frechet Distribution
dgen_extreme_value	The Generalized Extreme Value Distribution
dhurdle_gamma	Hurdle Distributions
dhurdle_lognormal	Hurdle Distributions
dhurdle_negbinomial	Hurdle Distributions
dhurdle_poisson	Hurdle Distributions
diagnostic-quantities	Extract Diagnostic Quantities of 'brms' Models
dinv_gaussian	The Inverse Gaussian Distribution
Dirichlet	The Dirichlet Distribution
dirichlet	Special Family Functions for 'brms' Models
dlogistic_normal	The (Multivariate) Logistic Normal Distribution
dmulti_normal	The Multivariate Normal Distribution
dmulti_student_t	The Multivariate Student-t Distribution
draws-brms	Transform 'brmsfit' to 'draws' objects
draws-index-brms	Index 'brmsfit' objects
draws.	Index 'brmsfit' objects
dshifted_lnorm	The Shifted Log Normal Distribution
dskew_normal	The Skew-Normal Distribution
dstudent_t	The Student-t Distribution
dvon_mises	The von Mises Distribution
dwiener	The Wiener Diffusion Model Distribution
dzero_inflated_beta	Zero-Inflated Distributions
dzero_inflated_beta_binomial	Zero-Inflated Distributions
dzero_inflated_binomial	Zero-Inflated Distributions
dzero_inflated_negbinomial	Zero-Inflated Distributions
dzero_inflated_poisson	Zero-Inflated Distributions

-- E --

emmeans-brms-helpers	Support Functions for 'emmeans'
emm_basis.brmsfit	Support Functions for 'emmeans'
empty_prior	Prior Definitions for 'brms' Models
epilepsy	Epileptic seizure counts
ExGaussian	The Exponentially Modified Gaussian Distribution
exgaussian	Special Family Functions for 'brms' Models
exponential	Special Family Functions for 'brms' Models
expose_functions	Expose user-defined 'Stan' functions
expose_functions.brmsfit	Expose user-defined 'Stan' functions
expp1	Exponential function plus one.
extract_draws	Prepare Predictions

-- F --

family.brmsfit	Extract Model Family Objects
fcor	Fixed residual correlation (FCOR) structures
fitted.brmsfit	Expected Values of the Posterior Predictive Distribution
fixef	Extract Population-Level Estimates
fixef.brmsfit	Extract Population-Level Estimates
Frechet	The Frechet Distribution
frechet	Special Family Functions for 'brms' Models

-- G --

GenExtremeValue	The Generalized Extreme Value Distribution
gen_extreme_value	Special Family Functions for 'brms' Models
geometric	Special Family Functions for 'brms' Models
get_dpar	Draws of a Distributional Parameter
get_prior	Overview on Priors for 'brms' Models
get_refmodel.brmsfit	Projection Predictive Variable Selection: Get Reference Model
gp	Set up Gaussian process terms in 'brms'
gr	Set up basic grouping terms in 'brms'

-- H --

horseshoe	Regularized horseshoe priors in 'brms'
Hurdle	Hurdle Distributions
hurdle_cumulative	Special Family Functions for 'brms' Models
hurdle_gamma	Special Family Functions for 'brms' Models
hurdle_lognormal	Special Family Functions for 'brms' Models
hurdle_negbinomial	Special Family Functions for 'brms' Models
hurdle_poisson	Special Family Functions for 'brms' Models
hypothesis	Non-Linear Hypothesis Testing
hypothesis.brmsfit	Non-Linear Hypothesis Testing
hypothesis.default	Non-Linear Hypothesis Testing

-- I --

Index	Index 'brmsfit' objects
index	Additional Response Information
inhaler	Clarity of inhaler instructions
InvGaussian	The Inverse Gaussian Distribution
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_arma	Check if argument is a correlation structure
is.cor_brms	Check if argument is a correlation structure
is.cor_car	Check if argument is a correlation structure
is.cor_cosy	Check if argument is a correlation structure
is.cor_fixed	Check if argument is a correlation structure
is.cor_sar	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
iterations,	Index 'brmsfit' objects

-- K --

kfold	K-Fold Cross-Validation
kfold.brmsfit	K-Fold Cross-Validation
kfold_predict	Predictions from K-Fold Cross-Validation
kidney	Infections in kidney patients

-- L --

lasso	Set up a lasso prior in 'brms'
launch_shinystan	Interface to 'shinystan'
launch_shinystan.brmsfit	Interface to 'shinystan'
lf	Linear and Non-linear formulas in 'brms'
LogisticNormal	The (Multivariate) Logistic Normal Distribution
logistic_normal	Special Family Functions for 'brms' Models
logit_scaled	Scaled logit-link
logLik.brmsfit	Compute the Pointwise Log-Likelihood
logm1	Logarithm with a minus one offset.
lognormal	Special Family Functions for 'brms' Models
log_lik	Compute the Pointwise Log-Likelihood
log_lik.brmsfit	Compute the Pointwise Log-Likelihood
log_posterior	Extract Diagnostic Quantities of 'brms' Models
log_posterior.brmsfit	Extract Diagnostic Quantities of 'brms' Models
LOO	Efficient approximate leave-one-out cross-validation (LOO)
loo	Efficient approximate leave-one-out cross-validation (LOO)
LOO.brmsfit	Efficient approximate leave-one-out cross-validation (LOO)
loo.brmsfit	Efficient approximate leave-one-out cross-validation (LOO)
loo_compare	Model comparison with the 'loo' package
loo_compare.brmsfit	Model comparison with the 'loo' package
loo_linpred	Compute Weighted Expectations Using LOO
loo_linpred.brmsfit	Compute Weighted Expectations Using LOO
loo_model_weights	Model averaging via stacking or pseudo-BMA weighting.
loo_model_weights.brmsfit	Model averaging via stacking or pseudo-BMA weighting.
loo_moment_match	Moment matching for efficient approximate leave-one-out cross-validation
loo_moment_match.brmsfit	Moment matching for efficient approximate leave-one-out cross-validation
loo_predict	Compute Weighted Expectations Using LOO
loo_predict.brmsfit	Compute Weighted Expectations Using LOO
loo_predictive_interval	Compute Weighted Expectations Using LOO
loo_predictive_interval.brmsfit	Compute Weighted Expectations Using LOO
loo_R2	Compute a LOO-adjusted R-squared for regression models
loo_R2.brmsfit	Compute a LOO-adjusted R-squared for regression models
loo_subsample	Efficient approximate leave-one-out cross-validation (LOO) using subsampling
loo_subsample.brmsfit	Efficient approximate leave-one-out cross-validation (LOO) using subsampling
loss	Cumulative Insurance Loss Payments

-- M --

ma	Set up MA(q) correlation structures
make_conditions	Prepare Fully Crossed Conditions
make_stancode	Stan Code for 'brms' Models
make_standata	Data for 'brms' Models
marginal_effects	Display Conditional Effects of Predictors
marginal_effects.brmsfit	Display Conditional Effects of Predictors
marginal_smooths	Display Smooth Terms
marginal_smooths.brmsfit	Display Smooth Terms
mcmc_plot	MCMC Plots Implemented in 'bayesplot'
mcmc_plot.brmsfit	MCMC Plots Implemented in 'bayesplot'
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	Model Weighting Methods
model_weights.brmsfit	Model Weighting Methods
multinomial	Special Family Functions for 'brms' Models
MultiNormal	The Multivariate Normal Distribution
MultiStudentT	The Multivariate Student-t Distribution
mvbf	Set up a multivariate model formula for use in 'brms'
mvbind	Bind response variables in multivariate models
mvbrmsformula	Set up a multivariate model formula for use in 'brms'

-- N --

nchains	Index 'brmsfit' objects
nchains.brmsfit	Index 'brmsfit' objects
ndraws	Index 'brmsfit' objects
ndraws.brmsfit	Index 'brmsfit' objects
neff_ratio	Extract Diagnostic Quantities of 'brms' Models
neff_ratio.brmsfit	Extract Diagnostic Quantities of 'brms' Models
negbinomial	Special Family Functions for 'brms' Models
ngrps	Number of Grouping Factor Levels
ngrps.brmsfit	Number of Grouping Factor Levels
niterations	Index 'brmsfit' objects
niterations.brmsfit	Index 'brmsfit' objects
nlf	Linear and Non-linear formulas in 'brms'
nsamples	(Deprecated) Number of Posterior Samples
nsamples.brmsfit	(Deprecated) Number of Posterior Samples
nuts_params	Extract Diagnostic Quantities of 'brms' Models
nuts_params.brmsfit	Extract Diagnostic Quantities of 'brms' Models
nvariables	Index 'brmsfit' objects
nvariables.brmsfit	Index 'brmsfit' objects

-- O --

opencl

GPU support in Stan via OpenCL

-- P --

pairs.brmsfit	Create a matrix of output plots from a 'brmsfit' object
parnames	Extract Parameter Names
parnames.brmsfit	Extract Parameter Names
parse_bf	Parse Formulas of 'brms' Models
pasym_laplace	The Asymmetric Laplace Distribution
pbeta_binomial	The Beta-binomial Distribution
pexgaussian	The Exponentially Modified Gaussian Distribution
pfrechet	The Frechet Distribution
pgen_extreme_value	The Generalized Extreme Value Distribution
phurdle_gamma	Hurdle Distributions
phurdle_lognormal	Hurdle Distributions
phurdle_negbinomial	Hurdle Distributions
phurdle_poisson	Hurdle Distributions
pinv_gaussian	The Inverse Gaussian Distribution
plot.brmsfit	Trace and Density Plots for MCMC Draws
plot.brmshypothesis	Descriptions of 'brmshypothesis' Objects
plot.brms_conditional_effects	Display Conditional Effects of Predictors
posterior_average	Posterior draws of parameters averaged across models
posterior_average.brmsfit	Posterior draws of parameters averaged across models
posterior_epred	Draws from the Expected Value of the Posterior Predictive Distribution
posterior_epred.brmsfit	Draws from the Expected Value of the Posterior Predictive Distribution
posterior_interval	Compute posterior uncertainty intervals
posterior_interval.brmsfit	Compute posterior uncertainty intervals
posterior_linpred	Posterior Draws of the Linear Predictor
posterior_linpred.brmsfit	Posterior Draws of the Linear Predictor
posterior_predict	Draws from the Posterior Predictive Distribution
posterior_predict.brmsfit	Draws from the Posterior Predictive Distribution
posterior_samples	(Deprecated) Extract Posterior Samples
posterior_samples.brmsfit	(Deprecated) Extract Posterior Samples
posterior_smooths	Posterior Predictions of Smooth Terms
posterior_smooths.brmsfit	Posterior Predictions of Smooth Terms
posterior_summary	Summarize Posterior draws
posterior_summary.brmsfit	Summarize Posterior draws
posterior_summary.default	Summarize Posterior draws
posterior_table	Table Creation for Posterior Draws
post_prob	Posterior Model Probabilities from Marginal Likelihoods
post_prob.brmsfit	Posterior Model Probabilities from Marginal Likelihoods
pp_average	Posterior predictive draws averaged across models
pp_average.brmsfit	Posterior predictive draws averaged across models
pp_check	Posterior Predictive Checks for 'brmsfit' Objects
pp_check.brmsfit	Posterior Predictive Checks for 'brmsfit' Objects
pp_expect	Draws from the Expected Value of the Posterior Predictive Distribution
pp_mixture	Posterior Probabilities of Mixture Component Memberships
pp_mixture.brmsfit	Posterior Probabilities of Mixture Component Memberships
predict.brmsfit	Draws from the Posterior Predictive Distribution
predictive_error	Posterior Draws of Predictive Errors
predictive_error.brmsfit	Posterior Draws of Predictive Errors
predictive_interval	Predictive Intervals
predictive_interval.brmsfit	Predictive Intervals
prepare_predictions	Prepare Predictions
prepare_predictions.brmsfit	Prepare Predictions
print.brmsfit	Print a summary for a fitted model represented by a 'brmsfit' object
print.brmshypothesis	Descriptions of 'brmshypothesis' Objects
print.brmsprior	Print method for 'brmsprior' objects
print.brmssummary	Print a summary for a fitted model represented by a 'brmsfit' object
prior	Prior Definitions for 'brms' Models
prior_	Prior Definitions for 'brms' Models
prior_draws	Extract Prior Draws
prior_draws.brmsfit	Extract Prior Draws
prior_samples	Extract Prior Draws
prior_string	Prior Definitions for 'brms' Models
prior_summary	Extract Priors of a Bayesian Model Fitted with 'brms'
prior_summary.brmsfit	Extract Priors of a Bayesian Model Fitted with 'brms'
pshifted_lnorm	The Shifted Log Normal Distribution
pskew_normal	The Skew-Normal Distribution
pstudent_t	The Student-t Distribution
pvon_mises	The von Mises Distribution
pzero_inflated_beta	Zero-Inflated Distributions
pzero_inflated_beta_binomial	Zero-Inflated Distributions
pzero_inflated_binomial	Zero-Inflated Distributions
pzero_inflated_negbinomial	Zero-Inflated Distributions
pzero_inflated_poisson	Zero-Inflated Distributions

-- Q --

qasym_laplace	The Asymmetric Laplace Distribution
qfrechet	The Frechet Distribution
qgen_extreme_value	The Generalized Extreme Value Distribution
qshifted_lnorm	The Shifted Log Normal Distribution
qskew_normal	The Skew-Normal Distribution
qstudent_t	The Student-t Distribution

-- R --

R2D2	R2-D2 Priors in 'brms'
ranef	Extract Group-Level Estimates
ranef.brmsfit	Extract Group-Level Estimates
rasym_laplace	The Asymmetric Laplace Distribution
rate	Additional Response Information
rbeta_binomial	The Beta-binomial Distribution
rdirichlet	The Dirichlet Distribution
recompile_model	Recompile Stan models in 'brmsfit' objects
recover_data.brmsfit	Support Functions for 'emmeans'
reloo	Compute exact cross-validation for problematic observations
reloo.brmsfit	Compute exact cross-validation for problematic observations
reloo.loo	Compute exact cross-validation for problematic observations
rename_pars	Rename Parameters
residuals.brmsfit	Posterior Draws of Residuals/Predictive Errors
resp_cat	Additional Response Information
resp_cens	Additional Response Information
resp_dec	Additional Response Information
resp_index	Additional Response Information
resp_mi	Additional Response Information
resp_rate	Additional Response Information
resp_se	Additional Response Information
resp_subset	Additional Response Information
resp_thres	Additional Response Information
resp_trials	Additional Response Information
resp_trunc	Additional Response Information
resp_vint	Additional Response Information
resp_vreal	Additional Response Information
resp_weights	Additional Response Information
restructure	Restructure Old 'brmsfit' Objects
rexgaussian	The Exponentially Modified Gaussian Distribution
rfrechet	The Frechet Distribution
rgen_extreme_value	The Generalized Extreme Value Distribution
rhat	Extract Diagnostic Quantities of 'brms' Models
rhat.brmsfit	Extract Diagnostic Quantities of 'brms' Models
rinv_gaussian	The Inverse Gaussian Distribution
rlogistic_normal	The (Multivariate) Logistic Normal Distribution
rmulti_normal	The Multivariate Normal Distribution
rmulti_student_t	The Multivariate Student-t Distribution
rows2labels	Convert Rows to Labels
rshifted_lnorm	The Shifted Log Normal Distribution
rskew_normal	The Skew-Normal Distribution
rstudent_t	The Student-t Distribution
rvon_mises	The von Mises Distribution
rwiener	The Wiener Diffusion Model Distribution

-- S --

s	Defining smooths in 'brms' formulas
sar	Spatial simultaneous autoregressive (SAR) structures
save_pars	Control Saving of Parameter Draws
se	Additional Response Information
set_mecor	Linear and Non-linear formulas in 'brms'
set_nl	Linear and Non-linear formulas in 'brms'
set_prior	Prior Definitions for 'brms' Models
set_rescor	Linear and Non-linear formulas in 'brms'
Shifted_Lognormal	The Shifted Log Normal Distribution
shifted_lognormal	Special Family Functions for 'brms' Models
SkewNormal	The Skew-Normal Distribution
skew_normal	Special Family Functions for 'brms' Models
sratio	Special Family Functions for 'brms' Models
stancode	Extract Stan model code
stancode.brmsfit	Extract Stan model code
standata	Extract data passed to Stan
standata.brmsfit	Extract data passed to Stan
stanplot	MCMC Plots Implemented in 'bayesplot'
stanplot.brmsfit	MCMC Plots Implemented in 'bayesplot'
stanvar	User-defined variables passed to Stan
stanvars	User-defined variables passed to Stan
student	Special Family Functions for 'brms' Models
StudentT	The Student-t Distribution
subset	Additional Response Information
summary.brmsfit	Create a summary of a fitted model represented by a 'brmsfit' object

-- T --

t2	Defining smooths in 'brms' formulas
theme_black	(Deprecated) Black Theme for 'ggplot2' Graphics
theme_default	Default 'bayesplot' Theme for 'ggplot2' Graphics
threading	Threading in Stan
thres	Additional Response Information
trials	Additional Response Information
trunc	Additional Response Information

-- U --

unstr	Set up UNSTR correlation structures
update.brmsfit	Update 'brms' models
update.brmsfit_multiple	Update 'brms' models based on multiple data sets
update_adterms	Update Formula Addition Terms

-- V --

validate_newdata	Validate New Data
validate_prior	Validate Prior for 'brms' Models
VarCorr	Extract Variance and Correlation Components
VarCorr.brmsfit	Extract Variance and Correlation Components
variables	Index 'brmsfit' objects
variables,	Index 'brmsfit' objects
variables.brmsfit	Index 'brmsfit' objects
vcov.brmsfit	Covariance and Correlation Matrix of Population-Level Effects
vint	Additional Response Information
VonMises	The von Mises Distribution
von_mises	Special Family Functions for 'brms' Models
vreal	Additional Response Information

-- W --

WAIC	Widely Applicable Information Criterion (WAIC)
waic	Widely Applicable Information Criterion (WAIC)
WAIC.brmsfit	Widely Applicable Information Criterion (WAIC)
waic.brmsfit	Widely Applicable Information Criterion (WAIC)
weibull	Special Family Functions for 'brms' Models
weights	Additional Response Information
Wiener	The Wiener Diffusion Model Distribution
wiener	Special Family Functions for 'brms' Models

-- Z --

ZeroInflated	Zero-Inflated Distributions
zero_inflated_beta	Special Family Functions for 'brms' Models
zero_inflated_beta_binomial	Special Family Functions for 'brms' Models
zero_inflated_binomial	Special Family Functions for 'brms' Models
zero_inflated_negbinomial	Special Family Functions for 'brms' Models
zero_inflated_poisson	Special Family Functions for 'brms' Models
zero_one_inflated_beta	Special Family Functions for 'brms' Models