Bayesian Probit Choice Modeling

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Documentation for package ‘RprobitB’ version 1.2.0

• 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	Preference-based classification of deciders
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
d_to_gamma	Transform increments to thresholds
fit_model	Fit probit model to choice data
get_cov	Extract covariates of choice occasion
gibbs_sampler	Gibbs sampler for probit models
ll_ordered	Compute ordered probit log-likelihood
mml	Approximate marginal model likelihood
model_selection	Compare fitted models
mode_approx	Gibbs sample mode
npar	Extract number of model parameters
npar.RprobitB_fit	Extract number of model parameters
overview_effects	Print effect overview
plot.RprobitB_coef	Extract model effects
plot.RprobitB_fit	Visualize fitted probit model
plot.RprobitB_mml	Approximate marginal model likelihood
plot_class_allocation	Plot class allocation (for 'P_r = 2' only)
plot_mixture_contour	Plot bivariate contour of mixing distributions
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
print.RprobitB_coef	Extract model effects
print.RprobitB_mml	Approximate marginal model likelihood
print.RprobitB_model_selection	Compare fitted models
print.RprobitB_parameter	Define probit model parameter
RprobitB_parameter	Define probit model parameter
R_hat	Compute Gelman-Rubin statistic
sample_allocation	Sample allocation
simulate_choices	Simulate choice data
train_choice	Stated Preferences for Train Traveling
train_test	Split choice data into train and test subset
transform.RprobitB_fit	Transform fitted probit model
update.RprobitB_fit	Update and re-fit probit model
update_b	Update class means
update_b_c	Update mean of a single class
update_classes_dp	Dirichlet process class updates
update_classes_wb	Weight-based class updates
update_coefficient	Update coefficient vector
update_d	Update utility threshold increments
update_m	Update class sizes
update_Omega	Update class covariances
update_Omega_c	Update covariance of a single class
update_s	Update class weight vector
update_Sigma	Update error covariance matrix
update_U	Update utility vector
update_U_ranked	Update ranked utility vector
update_z	Update class allocation vector