StanSimulate

Prepared individual level data from PrepareSimulationData

df_indiv

Prepared common data from PrepareSimulationData

df_common

Prepared simulation options from PrepareSimulationData

sim_options

Seed for pseudo-random number generator get_rng see help(get_rng, package = "rstan")

stan_seed

Use Stan functions to simulate Welfare and Demand

internal

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) <http://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.org/10.1016/j.jocm.2017.12.002>) for policy simulation.

StanSimulate: StanSimulate

Description

Usage

Arguments

Value