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rmdcev  

Kuhn-Tucker and Multiple Discrete-Continuous Extreme Value Models
View on CRAN: Click here


Download and install rmdcev package within the R console
Install from CRAN:
install.packages("rmdcev")

Install from Github:
library("remotes")
install_github("cran/rmdcev")

Install by package version:
library("remotes")
install_version("rmdcev", "1.2.5")



Attach the package and use:
library("rmdcev")
Maintained by
Patrick Lloyd-Smith
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-06-21
Latest Update: 2024-02-25
Description:
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) . The package also implements demand forecasting (Pinjari and Bhat (2011) ) and welfare calculation (Lloyd-Smith (2018) ) for policy simulation.
How to cite:
Patrick Lloyd-Smith (2019). rmdcev: Kuhn-Tucker and Multiple Discrete-Continuous Extreme Value Models. R package version 1.2.5, https://cran.r-project.org/web/packages/rmdcev. Accessed 06 Nov. 2024.
Previous versions and publish date:
0.9.0 (2019-06-21 17:00), 1.1.1 (2019-11-22 18:50), 1.2.0 (2020-08-14 14:40), 1.2.2 (2020-09-18 10:10), 1.2.3 (2020-09-23 08:30), 1.2.4 (2020-09-30 20:40), 1.2.5 (2023-03-30 18:10)
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