rmdcev: Kuhn-Tucker and Multiple Discrete-Continuous Extreme Value Models

Estimates and simulates Kuhn-Tucker demand models with individual heterogeneity. The package implements the multiple-discrete continuous extreme value (MDCEV) model and the Kuhn-Tucker specification common in the environmental economics literature on recreation demand. Latent class and random parameters specifications can be implemented and the models are fit using maximum likelihood estimation or Bayesian estimation. All models are implemented in Stan, which is a C++ package for performing full Bayesian inference (see Stan Development Team, 2019) <https://mc-stan.org/>. The package also implements demand forecasting (Pinjari and Bhat (2011) <https://repositories.lib.utexas.edu/handle/2152/23880>) and welfare calculation (Lloyd-Smith (2018) <doi:10.1016/j.jocm.2017.12.002>) for policy simulation.

Getting started

Package details

AuthorPatrick Lloyd-Smith [aut, cre], Trustees of Columbia University [cph]
MaintainerPatrick Lloyd-Smith <patrick.lloydsmith@usask.ca>
LicenseMIT + file LICENSE
Version1.2.5
URL https://github.com/plloydsmith/rmdcev
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("rmdcev")

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rmdcev documentation built on March 31, 2023, 6:49 p.m.