Bayesian Regression Models using Stan


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Documentation for package ‘brms’ version 2.0.1

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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
addition-terms Additional Response Information
add_ic Add information criteria and fit indices to fitted model objects
add_ic.brmsfit Add information criteria and fit indices to fitted model objects
add_ic<- Add information criteria and fit indices to fitted model objects
add_loo Add the LOO information criterion to fitted model objects
add_loo.brmsfit Add the LOO information criterion to fitted model objects
add_waic Add the WAIC to fitted model objects
add_waic.brmsfit Add the WAIC to fitted model objects
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

-- 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

-- C --

categorical Special Family Functions for 'brms' Models
coef.brmsfit Extract Model Coefficients
compare_ic Compare Information Criteria of Different Models
control_params Extract Control Parameters of the NUTS Sampler
control_params.brmsfit Extract Control Parameters of the NUTS Sampler
cor_ar AR(p) correlation structure
cor_arma ARMA(p,q) correlation structure
cor_arma-class ARMA(p,q) correlation structure
cor_arr ARR(r) correlation structure
cor_brms Correlation structure classes for the 'brms' package
cor_brms-class Correlation structure classes for the 'brms' package
cor_bsts Basic Bayesian Structural Time Series
cor_bsts-class Basic Bayesian Structural Time Series
cor_car Spatial conditional autoregressive (CAR) structures
cor_errorsar Spatial simultaneous autoregressive (SAR) structures
cor_fixed Fixed user-defined covariance matrices
cor_icar Spatial conditional autoregressive (CAR) structures
cor_lagsar Spatial simultaneous autoregressive (SAR) structures
cor_ma MA(q) correlation structure
cor_sar Spatial simultaneous autoregressive (SAR) structures
cov_fixed Fixed user-defined covariance matrices
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

-- D --

dasym_laplace The Asymmetric Laplace Distribution
dexgaussian The Exponentially Modified Gaussian Distribution
dfrechet The Frechet Distribution
dgen_extreme_value The Generalized Extreme Value Distribution
diagnostic-quantities Extract Diagnostic Quantities of 'brms' Models
dinv_gaussian The Inverse Gaussian Distribution
dmulti_normal The Multivariate Normal Distribution
dmulti_student_t The Multivariate Student-t 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

-- E --

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.

-- F --

fitted.brmsfit Extract Model Fitted Values of 'brmsfit' Objects
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 Set up a horseshoe prior in 'brms'
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.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_bsts Check if argument is a correlation structure
is.cor_car 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
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 Compute the LOO information criterion
loo Compute the LOO information criterion
LOO.brmsfit Compute the LOO information criterion
loo.brmsfit Compute the LOO information criterion
loo_linpred Compute Weighted Expectations Using LOO
loo_linpred.brmsfit Compute Weighted Expectations Using LOO
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

-- M --

make_stancode Stan Code for 'brms' Models
make_standata Data for 'brms' Models
marginal_effects Display marginal effects of predictors
marginal_effects.brmsfit Display marginal effects of predictors
marginal_smooths Display Smooth Terms
marginal_smooths.brmsfit Display Smooth Terms
me Predictors with Measurement Error in 'brms' Models
mixture Finite Mixture Families in 'brms'
mm Set up multi-membership grouping terms in 'brms'
mo Monotonic Predictors in 'brms' Models
mono Monotonic Predictors in 'brms' Models
monotonic Monotonic Predictors in 'brms' Models
MultiNormal The Multivariate Normal Distribution
MultiStudentT The Multivariate Student-t Distribution
mvbf Set up a multivariate model formula for use in 'brms'
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 levels
ngrps.brmsfit Number of 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
par.names Extract Parameter Names
par.names.brmsfit Extract Parameter Names
parnames Extract Parameter Names
parnames.brmsfit Extract Parameter Names
parse_bf Parse Formulas of 'brms' Models
parse_bf.brmsformula Parse Formulas of 'brms' Models
parse_bf.default Parse Formulas of 'brms' Models
parse_bf.mvbrmsformula 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
pinv_gaussian The Inverse Gaussian Distribution
plot.brmsfit Trace and Density Plots for MCMC Samples
plot.brmshypothesis Descriptions of 'brmshypothesis' Objects
plot.brmsMarginalEffects Display marginal effects of predictors
posterior.samples Extract posterior samples
posterior.samples.brmsfit Extract posterior samples
posterior_interval Compute posterior uncertainty intervals
posterior_interval.brmsfit Compute posterior uncertainty intervals
posterior_linpred Extract Model Fitted Values of 'brmsfit' Objects
posterior_linpred.brmsfit Extract Model Fitted Values of 'brmsfit' Objects
posterior_predict Model Predictions of 'brmsfit' Objects
posterior_predict.brmsfit Model Predictions of 'brmsfit' Objects
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_check Posterior Predictive Checks for 'brmsfit' Objects
pp_check.brmsfit Posterior Predictive Checks for 'brmsfit' Objects
pp_mixture Posterior Probabilities of Mixture Component Memberships
pp_mixture.brmsfit Posterior Probabilities of Mixture Component Memberships
predict.brmsfit Model Predictions of 'brmsfit' Objects
predictive_error Extract Model Residuals from brmsfit Objects
predictive_error.brmsfit Extract Model Residuals from brmsfit Objects
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'
pskew_normal The Skew-Normal Distribution
pstudent_t The Student-t Distribution
pvon_mises The von Mises Distribution

-- Q --

qasym_laplace The Asymmetric Laplace Distribution
qfrechet The Frechet 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
reloo Compute exact cross-validation for problematic observations
reloo.loo Compute exact cross-validation for problematic observations
residuals.brmsfit Extract Model Residuals from brmsfit Objects
resp_cat Additional Response Information
resp_cens Additional Response Information
resp_dec Additional Response Information
resp_se Additional Response Information
resp_trials Additional Response Information
resp_trunc 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
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
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'
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'
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 Black Theme for 'ggplot2' Graphics
theme_default Default 'bayesplot' Theme for 'ggplot2' Graphics

-- U --

update.brmsfit Update 'brms' models

-- V --

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 Compute the WAIC
waic Compute the WAIC
WAIC.brmsfit Compute the WAIC
waic.brmsfit Compute the WAIC
weibull Special Family Functions for 'brms' Models
Wiener The Wiener Diffusion Model Distribution
wiener Special Family Functions for 'brms' Models

-- Z --

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