Estimates different multiple discrete-continuous extreme value (MDCEV) demand model specifications with observed and unobserved individual heterogeneity (Bhat (2008) <doi:10.1016/j.trb.2007.06.002>). Fixed parameter, latent class, and random parameter models can be estimated. These models are estimated using maximum likelihood or Bayesian estimation techniques and are implemented in 'Stan', which is a C++ package for performing full Bayesian inference (see Stan Development Team (2018) <http://mc-stan.org>). The 'rmdcev' package also includes functions for demand simulation (Pinjari and Bhat (2011) <https://repositories.lib.utexas.edu/handle/2152/23880>) and welfare simulation (Lloyd-Smith (2018) <doi:10.1016/j.jocm.2017.12.002>).
|Author||Patrick Lloyd-Smith [aut, cre], Trustees of Columbia University [cph]|
|Maintainer||Patrick Lloyd-Smith <[email protected]>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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