R: Choice Models with Economic Foundation

# Choice Models with Economic Foundation

## Documentation for package ‘echoice2’ version 0.2.4

- DESCRIPTION file.
- 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