Bayesian Regression Models using 'Stan'
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Documentation for package ‘brms’ version 2.21.0
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A B C D E F G H I K L M N O 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_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.brmsprior | Transform into a brmsprior object |
| as.data.frame.brmsfit | Extract Posterior Draws |
| as.matrix.brmsfit | Extract Posterior Draws |
| as.mcmc | (Deprecated) Extract posterior samples for use with the 'coda' package |
| as.mcmc.brmsfit | (Deprecated) 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 |
| constant | Constant priors in 'brms' |
| 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 |
| default_prior | Default priors for Bayesian models |
| default_prior.default | Default Priors for 'brms' Models |
| 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 | Default priors for Bayesian 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 | (Defunct) 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 Bayesian models |
| make_standata | Stan data for Bayesian 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 | Priors of 'brms' models |
| prior_summary.brmsfit | Priors of 'brms' models |
| pshifted_lnorm | The Shifted Log Normal Distribution |
| psis | Pareto smoothed importance sampling (PSIS) |
| psis.brmsfit | Pareto smoothed importance sampling (PSIS) |
| 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 | R2D2 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 |
| read_csv_as_stanfit | Read CmdStan CSV files as a brms-formatted stanfit object |
| 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 in brmsfit objects |
| 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 R Objects |
| restructure.brmsfit | 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 | Stan Code for Bayesian models |
| stancode.brmsfit | Extract Stan code from 'brmsfit' objects |
| stancode.default | Stan Code for 'brms' Models |
| standata | Stan data for Bayesian models |
| standata.brmsfit | Extract data passed to Stan from 'brmsfit' objects |
| standata.default | Data for 'brms' Models |
| 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 |