We introduce advanced Bayesian choice modeling capabilities that extend beyond the traditional Multinomial Logit (MNL) model available in Sawtooth Software’s CBCHB programs. By leveraging the R packages RSGHB and Apollo, we will demonstrate fitting a diminishing returns component within a utility function in an MNL model, implementing a Hierarchical Bayes nested Logit model, estimating a joint discrete/continuous volumetric model. Our session will guide you through these concepts and demonstrate how to estimate these models in R using RSGHB and Apollo. Additionally, we will showcase how the latest version of Latent Gold can kick-start your modeling process by exporting code directly compatible with RSGHB.
