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>.">

echoice2: Choice Models with Economic Foundation (original) (raw)

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 ORCID iD [aut, cre]
Maintainer: Nino Hardt
BugReports: https://github.com/ninohardt/echoice2/issues
License: MIT + file
URL: https://github.com/ninohardt/echoice2,http://ninohardt.de/echoice2/
NeedsCompilation: yes
Materials: NEWS
CRAN checks: echoice2 results

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