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.

Version: 1.2.4
Depends: R (≥ 4.0.0), Rcpp (≥ 1.0.5), methods
Imports: rstan (≥ 2.21.0), rstantools (≥ 2.1.1), RcppParallel (≥ 5.0.1), dplyr (≥ 0.7.8), purrr, tibble, tidyr, utils, stats, Formula
LinkingTo: BH (≥ 1.72.0), Rcpp, RcppEigen (≥, RcppParallel (≥ 5.0.1), rstan (≥ 2.21.0), StanHeaders (≥ 2.21.0)
Suggests: knitr, rmarkdown, testthat
Published: 2020-09-30
Author: Patrick Lloyd-Smith [aut, cre], Trustees of Columbia University [cph]
Maintainer: Patrick Lloyd-Smith <patrick.lloydsmith at usask.ca>
BugReports: https://github.com/plloydsmith/rmdcev/issues
License: MIT + file LICENSE
URL: https://github.com/plloydsmith/rmdcev
NeedsCompilation: yes
SystemRequirements: GNU make
Citation: rmdcev citation info
Materials: README NEWS
CRAN checks: rmdcev results


Reference manual: rmdcev.pdf
Package source: rmdcev_1.2.4.tar.gz
Windows binaries: r-devel: rmdcev_1.2.4.zip, r-release: rmdcev_1.2.4.zip, r-oldrel: rmdcev_1.2.3.zip
macOS binaries: r-release: rmdcev_1.2.4.tgz, r-oldrel: not available
Old sources: rmdcev archive


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