Implements choice models based on economic theory, including estimation using Markov chain Monte Carlo (MCMC), prediction, and more. Its usability is inspired by ideas from 'tidyverse'. Models include versions of the Hierarchical Multinomial Logit and Multiple Discrete-Continous (Volumetric) models with and without screening. The foundations of these models are described in Allenby, Hardt and Rossi (2019) <doi:10.1016/bs.hem.2019.04.002>. Models with conjunctive screening are described in Kim, Hardt, Kim and Allenby (2022) <doi:10.1016/j.ijresmar.2022.04.001>. Models with set-size variation are described in Hardt and Kurz (2020) <doi:10.2139/ssrn.3418383>.
Version: 0.2.4 Depends: R (≥ 3.5), dplyr, ggplot2 Imports: Rcpp, parallel, magrittr, stats, graphics, stringr, purrr, tibble, tidyselect, tidyr, rlang, forcats LinkingTo: Rcpp, RcppArmadillo Suggests: knitr, rmarkdown, testthat, bayesm Published: 2023-11-20 DOI: 10.32614/CRAN.package.echoice2 Author: Nino Hardt [aut, cre] Maintainer: Nino Hardt <me at ninohardt.com> BugReports: https://github.com/ninohardt/echoice2/issues License: MIT + file LICENSE URL: https://github.com/ninohardt/echoice2, http://ninohardt.de/echoice2/ NeedsCompilation: yes Materials: NEWS CRAN checks: echoice2 results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=echoice2 to link to this page.
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