%.% |
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 |