# Bayesian Regression Models using 'Stan'

## Documentation for package ‘brms’ version 2.13.5

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## Help Pages

A B C D E F G H I K L M N P Q R S T U V W Z

brms-package | 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_waic | Add model fit criteria to model objects
ar | Set up AR(p) correlation structures
arma | Set up ARMA(p,q) correlation structures
as.array.brmsfit | Extract Posterior Samples
as.data.frame.brmsfit | Extract Posterior Samples
as.matrix.brmsfit | Extract Posterior Samples
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
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
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
categorical | Special Family Functions for 'brms' Models
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
ddirichlet | The Dirichlet Distribution
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
dmulti_normal | The Multivariate Normal Distribution
dmulti_student_t | The Multivariate Student-t Distribution
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_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_prior | Overview on Priors for 'brms' Models
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_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 --

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

## -- 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'
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

## -- 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 --

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
nlf | Linear and Non-linear formulas in 'brms'
nsamples | Number of Posterior Samples
nsamples.brmsfit | Number of Posterior Samples
nuts_params | Extract Diagnostic Quantities of 'brms' Models
nuts_params.brmsfit | Extract Diagnostic Quantities of 'brms' Models

## -- 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
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 Samples
plot.brmshypothesis | Descriptions of 'brmshypothesis' Objects
plot.brms_conditional_effects | Display Conditional Effects of Predictors
posterior_average | Posterior samples of parameters averaged across models
posterior_average.brmsfit | Posterior samples of parameters averaged across models
posterior_epred | Expected Values of the Posterior Predictive Distribution
posterior_epred.brmsfit | Expected Values of the Posterior Predictive Distribution
posterior_interval | Compute posterior uncertainty intervals
posterior_interval.brmsfit | Compute posterior uncertainty intervals
posterior_linpred | Posterior Samples of the Linear Predictor
posterior_linpred.brmsfit | Posterior Samples of the Linear Predictor
posterior_predict | Samples from the Posterior Predictive Distribution
posterior_predict.brmsfit | Samples from the Posterior Predictive Distribution
posterior_samples | Extract Posterior Samples
posterior_samples.brmsfit | Extract Posterior Samples
posterior_summary | Summarize Posterior Samples
posterior_summary.brmsfit | Summarize Posterior Samples
posterior_summary.default | Summarize Posterior Samples
posterior_table | Table Creation for Posterior Samples
post_prob | Posterior Model Probabilities from Marginal Likelihoods
post_prob.brmsfit | Posterior Model Probabilities from Marginal Likelihoods
pp_average | Posterior predictive samples averaged across models
pp_average.brmsfit | Posterior predictive samples averaged across models
pp_check | Posterior Predictive Checks for 'brmsfit' Objects
pp_check.brmsfit | Posterior Predictive Checks for 'brmsfit' Objects
pp_expect | Expected Values of the Posterior Predictive Distribution
pp_mixture | Posterior Probabilities of Mixture Component Memberships
pp_mixture.brmsfit | Posterior Probabilities of Mixture Component Memberships
predict.brmsfit | Samples from the Posterior Predictive Distribution
predictive_error | Posterior Samples of Predictive Errors
predictive_error.brmsfit | Posterior Samples 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_samples | Extract prior samples
prior_samples.brmsfit | Extract prior samples
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_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
qshifted_lnorm | The Shifted Log Normal Distribution
qskew_normal | The Skew-Normal Distribution
qstudent_t | The Student-t Distribution

## -- R --

ranef | Extract Group-Level Estimates
ranef.brmsfit | Extract Group-Level Estimates
rasym_laplace | The Asymmetric Laplace Distribution
rdirichlet | The Dirichlet Distribution
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 Samples of Residuals/Predictive Errors
resp_cat | Additional Response Information
resp_cens | Additional Response Information
resp_dec | 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
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
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
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

## -- U --

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
VarCorr | Extract Variance and Correlation Components
VarCorr.brmsfit | Extract Variance and Correlation Components
vcov.brmsfit | Covariance and Correlation Matrix of Population-Level Effects
VonMises | The von Mises Distribution
von_mises | Special Family Functions for 'brms' Models

## -- 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
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_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