Bayesian Probit Choice Modeling

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Documentation for package ‘RprobitB’ version 1.1.4

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

as_cov_names	Re-label alternative specific covariates
check_form	Check model formula
check_prior	Check prior parameters
choice_probabilities	Compute choice probabilities
classification	Classify deciders preference-based
coef.RprobitB_fit	Extract model effects
compute_p_si	Compute choice probabilities at posterior samples
cov_mix	Extract estimated covariance matrix of mixing distribution
create_lagged_cov	Create lagged choice covariates
fit_model	Fit probit model to choice data
get_cov	Extract covariates of choice occasion
mml	Approximate marginal model likelihood
model_selection	Compare fitted models
npar	Extract number of model parameters
npar.RprobitB_fit	Extract number of model parameters
overview_effects	Print effect overview
plot.RprobitB_data	Visualize choice data
plot.RprobitB_fit	Visualize fitted probit model
plot_roc	Plot ROC curve
point_estimates	Compute point estimates
predict.RprobitB_fit	Predict choices
pred_acc	Compute prediction accuracy
prepare_data	Prepare choice data for estimation
RprobitB_parameter	Define probit model parameter
R_hat	Compute Gelman-Rubin statistic
simulate_choices	Simulate choice data
train_choice	Stated Preferences for Train Traveling
train_test	Split choice data in train and test subset
transform.RprobitB_fit	Transform fitted probit model
update.RprobitB_fit	Update and re-fit probit model