Package index

Fit models

Fit empirical data or simulate and fit a specified model.

fit()

Fit a Bayesian probit choice model

update(<RprobitB_fit>)

Update and refit a choice model

Posterior analysis

Summarize, extract, and visualize posterior draws.

print(<RprobitB_fit>)

Print a fitted choice model

summary(<RprobitB_fit>)

Summarize a fitted choice model

print(<summary.RprobitB_fit>)

Print a fitted model summary

latent_class_diagnostics()

Diagnose latent-class occupancy and membership

coef(<RprobitB_fit>)

Extract posterior coefficient summaries

vcov(<RprobitB_fit>)

Extract the posterior covariance matrix

confint(<RprobitB_fit>)

Compute posterior credible intervals

interpret() print(<RprobitB_interpretation>)

Interpret the estimates of a fitted choice model

as_draws(<RprobitB_fit>)

Convert a fitted model to posterior draws

plot(<RprobitB_fit>)

Plot posterior draws

Prediction and accessors

Predict choices, inspect residuals, and extract fitted model information.

predict(<RprobitB_fit>)

Predict choices

residuals(<RprobitB_fit>)

Extract choice residuals

reexports train_test

Objects exported from other packages

formula(<RprobitB_fit>)

Extract the fitted formula

model.frame(<RprobitB_fit>)

Extract the fitted data

nobs(<RprobitB_fit>)

Count independent likelihood units

logLik(<RprobitB_fit>)

Extract the fitted log-likelihood

Bayesian model evaluation

Compare predictive performance and model evidence.

WAIC()

Compute the widely applicable information criterion

loo()

Compute approximate leave-one-out cross-validation

bayes_factor()

Compare models with a Bayes factor

Sampler kernels

Low-level functions for extending or testing the Gibbs sampler.

sample_allocation() update_s() update_z() update_m() update_classes_wb() update_classes_dp()

Update latent classes

update_coefficient() update_b_c() update_b() update_Omega_c() update_Omega()

Update coefficient distributions

d_to_gamma() log_likelihood_ordered() update_Sigma() update_U() update_U_ranked() update_d()

Update utilities and thresholds