Man pages for paul-buerkner/brms
Bayesian Regression Models using Stan

add_icAdd information criteria and fit indices to fitted model...
addition-termsAdditional Response Information
add_looAdd the LOO information criterion to fitted model objects
add_waicAdd the WAIC to fitted model objects
as.mcmc.brmsfitExtract posterior samples for use with the 'coda' package
AsymLaplaceThe Asymmetric Laplace Distribution
bayes_factor.brmsfitBayes Factors from Marginal Likelihoods
bayes_R2.brmsfitCompute a Bayesian version of R-squared for regression models
bridge_sampler.brmsfitLog Marginal Likelihood via Bridge Sampling
brmFit Bayesian Generalized (Non-)Linear Multivariate Multilevel...
brm_multipleRun the same 'brms' model on multiple datasets
brmsfamilySpecial Family Functions for 'brms' Models
brmsfit-classClass 'brmsfit' of models fitted with the 'brms' package
brmsformulaSet up a model formula for use in 'brms'
brmsformula-helpersLinear and Non-linear formulas in 'brms'
brmshypothesisDescriptions of 'brmshypothesis' Objects
brms-packageBayesian Regression Models using Stan
coef.brmsfitExtract Model Coefficients
combine_modelsCombine Models fitted with 'brms'
compare_icCompare Information Criteria of Different Models
control_paramsExtract Control Parameters of the NUTS Sampler
cor_arAR(p) correlation structure
cor_armaARMA(p,q) correlation structure
cor_arrARR(r) correlation structure
cor_brmsCorrelation structure classes for the 'brms' package
cor_bstsBasic Bayesian Structural Time Series
cor_carSpatial conditional autoregressive (CAR) structures
cor_fixedFixed user-defined covariance matrices
cor_maMA(q) correlation structure
cor_sarSpatial simultaneous autoregressive (SAR) structures
csCategory Specific Predictors in 'brms' Models
diagnostic-quantitiesExtract Diagnostic Quantities of 'brms' Models
epilepsyEpileptic seizure counts
ExGaussianThe Exponentially Modified Gaussian Distribution
expose_functionsExpose user-defined 'Stan' functions
expp1Exponential function plus one.
fitted.brmsfitExtract Model Fitted Values of 'brmsfit' Objects
fixef.brmsfitExtract Population-Level Estimates
FrechetThe Frechet Distribution
GenExtremeValueThe Generalized Extreme Value Distribution
get_priorOverview on Priors for 'brms' Models
gpSet up Gaussian process terms in 'brms'
grSet up basic grouping terms in 'brms'
horseshoeSet up a horseshoe prior in 'brms'
hypothesisNon-Linear Hypothesis Testing
inhalerClarity of inhaler instructions
InvGaussianThe Inverse Gaussian Distribution
inv_logit_scaledScaled inverse logit-link
is.brmsfitChecks if argument is a 'brmsfit' object
is.brmsformulaChecks if argument is a 'brmsformula' object
is.brmspriorChecks if argument is a 'brmsprior' object
is.brmstermsChecks if argument is a 'brmsterms' object
is.cor_brmsCheck if argument is a correlation structure
is.mvbrmsformulaChecks if argument is a 'mvbrmsformula' object
is.mvbrmstermsChecks if argument is a 'mvbrmsterms' object
kfoldK-Fold Cross-Validation
kidneyInfections in kidney patients
lassoSet up a lasso prior in 'brms'
launch_shinystan.brmsfitInterface to 'shinystan'
logit_scaledScaled logit-link
log_lik.brmsfitCompute the Pointwise Log-Likelihood
logm1Logarithm with a minus one offset.
LOOCompute the LOO information criterion
loo_predict.brmsfitCompute Weighted Expectations Using LOO
make_stancodeStan Code for 'brms' Models
make_standataData for 'brms' Models
marginal_effectsDisplay marginal effects of predictors
marginal_smoothsDisplay Smooth Terms
mePredictors with Measurement Error in 'brms' Models
mixtureFinite Mixture Families in 'brms'
mmSet up multi-membership grouping terms in 'brms'
moMonotonic Predictors in 'brms' Models
MultiNormalThe Multivariate Normal Distribution
MultiStudentTThe Multivariate Student-t Distribution
mvbrmsformulaSet up a multivariate model formula for use in 'brms'
ngrpsNumber of levels
nsamplesNumber of Posterior Samples
pairs.brmsfitCreate a matrix of output plots from a 'brmsfit' object
parnamesExtract Parameter Names
parse_bfParse Formulas of 'brms' Models
plot.brmsfitTrace and Density Plots for MCMC Samples
posterior_interval.brmsfitCompute posterior uncertainty intervals
posterior_samplesExtract posterior samples
posterior_summarySummarize Posterior Samples
posterior_tableTable Creation for Posterior Samples
post_prob.brmsfitPosterior Model Probabilities from Marginal Likelihoods
pp_check.brmsfitPosterior Predictive Checks for 'brmsfit' Objects
pp_mixturePosterior Probabilities of Mixture Component Memberships
predict.brmsfitModel Predictions of 'brmsfit' Objects
print.brmsfitPrint a summary for a fitted model represented by a 'brmsfit'...
print.brmspriorPrint method for 'brmsprior' objects
prior_samplesExtract prior samples
prior_summary.brmsfitExtract Priors of a Bayesian Model Fitted with 'brms'
ranef.brmsfitExtract Group-Level Estimates
relooCompute exact cross-validation for problematic observations
residuals.brmsfitExtract Model Residuals from brmsfit Objects
restructureRestructure Old 'brmsfit' Objects
sDefining smooths in 'brms' formulas
set_priorPrior Definitions for 'brms' Models
SkewNormalThe Skew-Normal Distribution
stancodeExtract Stan model code
standataExtract Data passed to Stan
stanplotMCMC Plots Implemented in 'bayesplot'
StudentTThe Student-t Distribution
summary.brmsfitCreate a summary of a fitted model represented by a 'brmsfit'...
theme_blackBlack Theme for 'ggplot2' Graphics
theme_defaultDefault 'bayesplot' Theme for 'ggplot2' Graphics
update.brmsfitUpdate 'brms' models
VarCorr.brmsfitExtract Variance and Correlation Components
vcov.brmsfitCovariance and Correlation Matrix of Population-Level Effects
VonMisesThe von Mises Distribution
WAICCompute the WAIC
WienerThe Wiener Diffusion Model Distribution
paul-buerkner/brms documentation built on Jan. 15, 2018, 3:12 a.m.