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 |
Reference manual: | echoice2.pdf |
Vignettes: |
Importing list-of-lists choice data and discrete choice modeling with echoice2 Volumetric Demand and Conjunctive Screening with echoice2 |
Package source: | echoice2_0.2.4.tar.gz |
Windows binaries: | r-devel: echoice2_0.2.4.zip, r-release: echoice2_0.2.4.zip, r-oldrel: echoice2_0.2.4.zip |
macOS binaries: | r-release (arm64): echoice2_0.2.4.tgz, r-oldrel (arm64): echoice2_0.2.4.tgz, r-release (x86_64): echoice2_0.2.4.tgz, r-oldrel (x86_64): echoice2_0.2.4.tgz |
Old sources: | echoice2 archive |
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