ec_undummy_lowhigh

Convert dummy-coded variables to low/high factor

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>.

Nino Hardt

echoice2

Choice Models with Economic Foundation

ec_undummy_lowhigh function

<dl><dt>vec_in</dt>
<dd>A vector of dummy-coded variables (0/1)</dd></dl>

Arguments

Convert dummy-coded variables to low/high factor — ec_undummy_lowhigh

<dl>

<dt>vec_in</dt>
<dd>A vector of dummy-coded variables (0/1)</dd>

</dl>

ec_undummy_lowhigh: Convert dummy-coded variables to low/high factor

Description

Usage

Value

Arguments

Examples