Perform hierarchical Bayesian Aldrich-McKelvey scaling using Hamiltonian Monte
Carlo via 'Stan'. Aldrich-McKelvey ('AM') scaling is a method for estimating the latent
positions of survey respondents and external objects on a common scale using positional survey
data. The hierarchical versions of the Bayesian 'AM' model included in this package outperform
other versions both in terms of yielding meaningful posterior distributions for respondent
positions and in terms of recovering true respondent positions in simulations. The package
contains functions for preparing data, fitting models, extracting estimates, plotting key
results, and comparing models using cross-validation. The original version of the default
model is described in Bølstad (2024)