Choice Models with Economic Foundation

---

Documentation for package ‘echoice2’ version 0.2.4

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

Help Pages

%.%	Get the attribute of an object
dd_dem	Discrete Choice Predictions (HMNL)
dd_dem_sr	Discrete Choice Predictions (HMNL with attribute-based screening)
dd_est_hmnl	Estimate discrete choice model (HMNL)
dd_est_hmnl_screen	Estimate discrete choice model (HMNL, attribute-based screening (not including price))
dd_LL	Log-Likelihood for compensatory hmnl model
dd_LL_sr	Log-Likelihood for screening hmnl model
dummify	Create dummy variables within a tibble
dummyvar	Dummy-code a categorical variable
ec_boxplot_MU	Generate MU_theta boxplot
ec_boxplot_screen	Generate Screening probability boxplot
ec_demcurve	Create demand curves
ec_demcurve_cond_dem	Create demand-incidence curves
ec_demcurve_inci	Create demand-incidence curves
ec_dem_aggregate	Aggregate posterior draws of demand
ec_dem_eval	Evaluate (hold-out) demand predictions
ec_dem_summarise	Summarize posterior draws of demand
ec_dem_summarize	Summarize posterior draws of demand
ec_draws_MU	Obtain MU_theta draws
ec_draws_screen	Obtain Screening probability draws
ec_estimates_MU	Obtain upper level model estimates
ec_estimates_screen	Summarize attribute-based screening parameters
ec_estimates_SIGMA	Obtain posterior mean estimates of upper level covariance
ec_estimates_SIGMA_corr	Obtain posterior mean estimates of upper level correlations
ec_gen_err_ev1	Simulate error realization from EV1 distribution
ec_gen_err_normal	Simulate error realization from Normal distribution
ec_lmd_NR	Obtain Log Marginal Density from draw objects
ec_lol_tidy1	Convert "list of lists" format to long "tidy" format
ec_screenprob_sr	Screening probabilities of choice alternatives
ec_screen_summarise	Summarize posterior draws of screening
ec_screen_summarize	Summarize posterior draws of screening
ec_summarise_attrlvls	Summarize attributes and levels
ec_summarize_attrlvls	Summarize attributes and levels
ec_trace_MU	Generate MU_theta traceplot
ec_trace_screen	Generate Screening probability traceplots
ec_undummy	Converts a set of dummy variables into a single categorical variable
ec_undummy_lowhigh	Convert dummy-coded variables to low/high factor
ec_undummy_lowmediumhigh	Convert dummy-coded variables to low/medium/high factor
ec_undummy_yesno	Convert dummy-coded variables to yes/no factor
ec_util_choice_to_long	Convert a vector of choices to long format
ec_util_dummy_mutualeclusive	Find mutually exclusive columns
get_attr_lvl	Obtain attributes and levels from tidy choice data with dummies
icecream	icecream
icecream_discrete	icecream_discrete
logMargDenNRu	Log Marginal Density (Newton-Raftery)
pizza	pizza
prep_newprediction	Match factor levels between two datasets
vd_add_prodid	Add product id to demand draws
vd_dem_summarise	Summarize posterior draws of demand (volumetric models only)
vd_dem_summarize	Summarize posterior draws of demand (volumetric models only)
vd_dem_vdm	Demand Prediction (Volumetric Demand Model)
vd_dem_vdm_screen	Demand Prediction (Volumetric demand, attribute-based screening)
vd_dem_vdm_ss	Demand Prediction (Volumetric demand, accounting for set-size variation, EV1 errors)
vd_est_vdm	Estimate volumetric demand model
vd_est_vdm_screen	Estimate volumetric demand model with attribute-based conjunctive screening
vd_est_vdm_ss	Estimate volumetric demand model accounting for set size variation (1st order)
vd_LL_vdm	Log-Likelihood for compensatory volumetric demand model
vd_LL_vdmss	Log-Likelihood for volumetric demand model with set-size variation
vd_LL_vdm_screen	Log-Likelihood for conjunctive-screening volumetric demand model
vd_long_tidy	Generate tidy choice data with dummies from long-format choice data
vd_prepare	Prepare choice data for analysis
vd_prepare_nox	Prepare choice data for analysis (without x being present)
vd_thin_draw	Thin 'echoice2'-vd draw objects