echoice2: Choice Models with Economic Foundation

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
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:

Reference manual:	echoice2.pdf
Vignettes:	Importing list-of-lists choice data and discrete choice modeling with echoice2 Volumetric Demand and Conjunctive Screening with echoice2

Downloads:

Package source:	echoice2_0.2.4.tar.gz
Windows binaries:	r-prerel: echoice2_0.2.4.zip, r-release: echoice2_0.2.4.zip, r-oldrel: echoice2_0.2.4.zip
macOS binaries:	r-prerel (arm64): echoice2_0.2.4.tgz, r-release (arm64): echoice2_0.2.4.tgz, r-oldrel (arm64): echoice2_0.2.4.tgz, r-prerel (x86_64): echoice2_0.2.4.tgz, r-release (x86_64): echoice2_0.2.4.tgz
Old sources:	echoice2 archive

Linking:

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