DESCRIPTION

Package: DEEPEst
Title: Hierarchical Bayesian Estimation for DEEP with 'Stan'
Version: 1.0
Date: 2019-05-09
Authors@R: 
    c(person(given = "Qi",
           family = "Zhao",
           role = c("aut", "cre"),
           email = "zhaoxiaomi277@outlook.com"),
      person(given = "Daniel",
           family = "Wall",
           role = c("ctb"),
           email = "itsdanwall@gmail.com"),
      person(given = "Center for Decision Sciences",
           family = "Columbia Business School",
           email = "cds@decisionsciences.columbia.edu",
           role = c("cph"))     
      )
Description: Dynamic Experiments for Estimating Preferences (DEEP) is a novel methodology to elicit individuals' risk and time preferences by dynamically optimizing the sequences of questions presented to each subject, while leveraging information about the distribution of the parameters across individuals (heterogeneity) and modeling response error explicitly. This package provides functions to execute hierarchical Bayesian estimation for DEEP with 'Stan' <https://mc-stan.org> and posterior analysis on estimates of both time and risk preferences parameters. 
License: GPL (>=3)
Encoding: UTF-8
LazyData: true
Biarch: true
Depends: 
    R (>= 3.4.0)
Imports: 
    methods,
    Rcpp (>= 0.12.0),
    rstan (>= 2.18.1),
    rstantools (>= 2.0.0)
LinkingTo: 
    BH (>= 1.66.0),
    Rcpp (>= 0.12.0),
    RcppEigen (>= 0.3.3.3.0),
    rstan (>= 2.18.1),
    StanHeaders (>= 2.18.0)
SystemRequirements: GNU make
RoxygenNote: 6.1.1