Man pages for brms
Bayesian Regression Models using 'Stan'
| add_criterion | Add model fit criteria to model objects |
| add_ic | Add model fit criteria to model objects |
| addition-terms | Additional Response Information |
| add_rstan_model | Add compiled 'rstan' models to 'brmsfit' objects |
| ar | Set up AR(p) correlation structures |
| arma | Set up ARMA(p,q) correlation structures |
| as.brmsprior | Transform into a brmsprior object |
| as.data.frame.brmsfit | Extract Posterior Draws |
| as.mcmc.brmsfit | (Deprecated) Extract posterior samples for use with the... |
| AsymLaplace | The Asymmetric Laplace Distribution |
| autocor.brmsfit | (Deprecated) Extract Autocorrelation Objects |
| autocor-terms | Autocorrelation structures |
| bayes_factor.brmsfit | Bayes Factors from Marginal Likelihoods |
| bayes_R2.brmsfit | Compute a Bayesian version of R-squared for regression models |
| BetaBinomial | The Beta-binomial Distribution |
| bridge_sampler.brmsfit | Log Marginal Likelihood via Bridge Sampling |
| brm | Fit Bayesian Generalized (Non-)Linear Multivariate Multilevel... |
| brm_multiple | Run the same 'brms' model on multiple datasets |
| brmsfamily | Special Family Functions for 'brms' Models |
| brmsfit-class | Class 'brmsfit' of models fitted with the 'brms' package |
| brmsfit_needs_refit | Check if cached fit can be used. |
| brmsformula | Set up a model formula for use in 'brms' |
| brmsformula-helpers | Linear and Non-linear formulas in 'brms' |
| brmshypothesis | Descriptions of 'brmshypothesis' Objects |
| brms-package | Bayesian Regression Models using 'Stan' |
| brmsterms | Parse Formulas of 'brms' Models |
| car | Spatial conditional autoregressive (CAR) structures |
| coef.brmsfit | Extract Model Coefficients |
| combine_models | Combine Models fitted with 'brms' |
| compare_ic | Compare Information Criteria of Different Models |
| conditional_effects.brmsfit | Display Conditional Effects of Predictors |
| conditional_smooths.brmsfit | Display Smooth Terms |
| constant | Constant priors in 'brms' |
| control_params | Extract Control Parameters of the NUTS Sampler |
| cor_ar | (Deprecated) AR(p) correlation structure |
| cor_arma | (Deprecated) ARMA(p,q) correlation structure |
| cor_arr | (Defunct) ARR correlation structure |
| cor_brms | (Deprecated) Correlation structure classes for the 'brms'... |
| cor_bsts | (Defunct) Basic Bayesian Structural Time Series |
| cor_car | (Deprecated) Spatial conditional autoregressive (CAR)... |
| cor_cosy | (Deprecated) Compound Symmetry (COSY) Correlation Structure |
| cor_fixed | (Deprecated) Fixed user-defined covariance matrices |
| cor_ma | (Deprecated) MA(q) correlation structure |
| cor_sar | (Deprecated) Spatial simultaneous autoregressive (SAR)... |
| cosy | Set up COSY correlation structures |
| create_priorsense_data.brmsfit | Prior sensitivity: Create priorsense data |
| cs | Category Specific Predictors in 'brms' Models |
| custom_family | Custom Families in 'brms' Models |
| data_predictor | Prepare Predictor Data |
| data_response | Prepare Response Data |
| default_prior | Default priors for Bayesian models |
| default_prior.default | Default Priors for 'brms' Models |
| density_ratio | Compute Density Ratios |
| diagnostic-quantities | Extract Diagnostic Quantities of 'brms' Models |
| Dirichlet | The Dirichlet Distribution |
| do_call | Execute a Function Call |
| draws-brms | Transform 'brmsfit' to 'draws' objects |
| draws-index-brms | Index 'brmsfit' objects |
| emmeans-brms-helpers | Support Functions for 'emmeans' |
| epilepsy | Epileptic seizure counts |
| ExGaussian | The Exponentially Modified Gaussian Distribution |
| expose_functions.brmsfit | Expose user-defined 'Stan' functions |
| expp1 | Exponential function plus one. |
| family.brmsfit | Extract Model Family Objects |
| fcor | Fixed residual correlation (FCOR) structures |
| fitted.brmsfit | Expected Values of the Posterior Predictive Distribution |
| fixef.brmsfit | Extract Population-Level Estimates |
| Frechet | The Frechet Distribution |
| GenExtremeValue | The Generalized Extreme Value Distribution |
| get_dpar | Draws of a Distributional Parameter |
| get_refmodel.brmsfit | Projection Predictive Variable Selection: Get Reference Model |
| get_y | Extract response values |
| gp | Set up Gaussian process terms in 'brms' |
| gr | Set up basic grouping terms in 'brms' |
| horseshoe | Regularized horseshoe priors in 'brms' |
| Hurdle | Hurdle Distributions |
| hypothesis.brmsfit | 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.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_brms | 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.brmsfit | K-Fold Cross-Validation |
| kfold_predict | Predictions from K-Fold Cross-Validation |
| kidney | Infections in kidney patients |
| lasso | (Defunct) Set up a lasso prior in 'brms' |
| launch_shinystan.brmsfit | Interface to 'shinystan' |
| LogisticNormal | The (Multivariate) Logistic Normal Distribution |
| logit_scaled | Scaled logit-link |
| log_lik.brmsfit | Compute the Pointwise Log-Likelihood |
| logm1 | Logarithm with a minus one offset. |
| loo.brmsfit | Efficient approximate leave-one-out cross-validation (LOO) |
| loo_compare.brmsfit | Model comparison with the 'loo' package |
| loo_model_weights.brmsfit | Model averaging via stacking or pseudo-BMA weighting. |
| loo_moment_match.brmsfit | Moment matching for efficient approximate leave-one-out... |
| loo_predict.brmsfit | Compute Weighted Expectations Using LOO |
| loo_R2.brmsfit | Compute a LOO-adjusted R-squared for regression models |
| loo_subsample.brmsfit | Efficient approximate leave-one-out cross-validation (LOO)... |
| loss | Cumulative Insurance Loss Payments |
| ma | Set up MA(q) correlation structures |
| make_conditions | Prepare Fully Crossed Conditions |
| 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.brmsfit | Model Weighting Methods |
| MultiNormal | The Multivariate Normal Distribution |
| MultiStudentT | The Multivariate Student-t Distribution |
| mvbind | Bind response variables in multivariate models |
| mvbrmsformula | Set up a multivariate model formula for use in 'brms' |
| ngrps.brmsfit | Number of Grouping Factor Levels |
| nsamples.brmsfit | (Deprecated) Number of Posterior Samples |
| opencl | GPU support in Stan via OpenCL |
| pairs.brmsfit | Create a matrix of output plots from a 'brmsfit' object |
| parnames | Extract Parameter Names |
| plot.brmsfit | Trace and Density Plots for MCMC Draws |
| posterior_average.brmsfit | Posterior draws of parameters averaged across models |
| posterior_epred.brmsfit | Draws from the Expected Value of the Posterior Predictive... |
| posterior_interval.brmsfit | Compute posterior uncertainty intervals |
| posterior_linpred.brmsfit | Posterior Draws of the Linear Predictor |
| posterior_predict.brmsfit | Draws from the Posterior Predictive Distribution |
| posterior_samples.brmsfit | (Deprecated) Extract Posterior Samples |
| posterior_smooths.brmsfit | Posterior Predictions of Smooth Terms |
| posterior_summary | Summarize Posterior draws |
| posterior_table | Table Creation for Posterior Draws |
| post_prob.brmsfit | Posterior Model Probabilities from Marginal Likelihoods |
| pp_average.brmsfit | Posterior predictive draws averaged across models |
| pp_check.brmsfit | Posterior Predictive Checks for 'brmsfit' Objects |
| pp_mixture.brmsfit | Posterior Probabilities of Mixture Component Memberships |
| predict.brmsfit | Draws from the Posterior Predictive Distribution |
| predictive_error.brmsfit | Posterior Draws of Predictive Errors |
| predictive_interval.brmsfit | Predictive Intervals |
| prepare_predictions | Prepare Predictions |
| print.brmsfit | Print a summary for a fitted model represented by a 'brmsfit'... |
| print.brmsprior | Print method for 'brmsprior' objects |
| prior_draws.brmsfit | Extract Prior Draws |
| prior_summary.brmsfit | Priors of 'brms' models |
| psis.brmsfit | Pareto smoothed importance sampling (PSIS) |
| R2D2 | R2D2 Priors in 'brms' |
| ranef.brmsfit | Extract Group-Level Estimates |
| read_csv_as_stanfit | Read CmdStan CSV files as a brms-formatted stanfit object |
| recompile_model | Recompile Stan models in 'brmsfit' objects |
| reloo.brmsfit | Compute exact cross-validation for problematic observations |
| rename_pars | Rename parameters in brmsfit objects |
| residuals.brmsfit | Posterior Draws of Residuals/Predictive Errors |
| restructure | Restructure Old R Objects |
| restructure.brmsfit | Restructure Old 'brmsfit' Objects |
| rows2labels | Convert Rows to Labels |
| s | Defining smooths in 'brms' formulas |
| sar | Spatial simultaneous autoregressive (SAR) structures |
| save_pars | Control Saving of Parameter Draws |
| set_prior | Prior Definitions for 'brms' Models |
| Shifted_Lognormal | The Shifted Log Normal Distribution |
| SkewNormal | The Skew-Normal Distribution |
| 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 |
| stanvar | User-defined variables passed to Stan |
| StudentT | The Student-t Distribution |
| summary.brmsfit | Create a summary of a fitted model represented by a 'brmsfit'... |
| theme_black | (Deprecated) Black Theme for 'ggplot2' Graphics |
| theme_default | Default 'bayesplot' Theme for 'ggplot2' Graphics |
| threading | Threading in Stan |
| unstr | Set up UNSTR correlation structures |
| update_adterms | Update Formula Addition Terms |
| update.brmsfit | Update 'brms' models |
| update.brmsfit_multiple | Update 'brms' models based on multiple data sets |
| validate_newdata | Validate New Data |
| validate_prior | Validate Prior for 'brms' Models |
| VarCorr.brmsfit | Extract Variance and Correlation Components |
| vcov.brmsfit | Covariance and Correlation Matrix of Population-Level Effects |
| VonMises | The von Mises Distribution |
| waic.brmsfit | Widely Applicable Information Criterion (WAIC) |
| Wiener | The Wiener Diffusion Model Distribution |
| ZeroInflated | Zero-Inflated Distributions |
