This function obtains proper posterior fit statistics. It computes the difference between true demand and each draw from the demand posterior. Then, fit statistics are obtained.
ec_dem_eval(de)demand draws (output from vd_dem_x function)
Predictive fit statistics (MAE, MSE, RAE, bias, hit-probability)
data(icecream) #run MCMC sampler (use way more than 50 draws for actual use) icecream_est <- icecream %>% dplyr::filter(id<100) %>% vd_est_vdm(R=100, keep=1) #Generate demand predictions icecream_predicted_demand= icecream %>% dplyr::filter(id<100) %>% vd_dem_vdm(icecream_est) #evaluate in-sample fit (note: too few draws for good results) ec_dem_eval(icecream_predicted_demand)