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 |
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 |
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 |
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 |
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 |
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. |
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 |
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' |
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 |
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 |
kfold | K-Fold Cross-Validation |
kfold.brmsfit | K-Fold Cross-Validation |
kidney | Infections in kidney patients |
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 |
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' |
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 |
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 |
qasym_laplace | The Asymmetric Laplace Distribution |
qfrechet | The Frechet Distribution |
qskew_normal | The Skew-Normal Distribution |
qstudent_t | The Student-t Distribution |
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 | 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 |
t2 | Defining smooths in 'brms' formulas |
theme_black | Black Theme for 'ggplot2' Graphics |
theme_default | Default 'bayesplot' Theme for 'ggplot2' Graphics |
update.brmsfit | Update 'brms' models |
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 |
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 |
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 |