Package: idealstan
Type: Package
Title: Bayesian IRT Ideal Point Models with 'Stan'
Version: 0.2.7
Date: 2018-02-07
Authors@R: c(person("Robert","Kubinec", role = c("aut","cre"),
                     email = "rmk7xy@virginia.edu"),
              person("Jonah", "Gabry", role = "ctb"),
              person("Ben", "Goodrich", role = "ctb"),
              person("Trustees of Columbia University",role='cph'))
BugReports: https://github.com/saudiwin/idealstan/issues
Description: Offers item-response theory (IRT) ideal-point scaling/dimension reduction methods that incorporate additional response categories and missing/censored values, including absences and abstentions, for roll call voting data (or any other kind of binary or ordinal item-response theory data). Full and approximate Bayesian inference is done via the 'Stan' engine (www.mc-stan.org). 
License: GPL
Depends: R (>= 3.1), Rcpp (>= 0.12.7)
Imports: rstan (>= 2.13.2), rstantools (>= 1.1.0), methods (>= 3.3.1),
        dplyr, tidyr, stringr, bayesplot, ggplot2, lazyeval, rlang,
        shinystan
Suggests: pscl, loo, knitr, rmarkdown
LinkingTo: StanHeaders (>= 2.13.1), rstan (>= 2.13.2), BH (>=
        1.62.0.1), Rcpp (>= 0.12.7), RcppEigen (>= 0.3.2.9.0)
RoxygenNote: 6.0.1
LazyData: false
VignetteBuilder: knitr
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2018-02-08 18:35:01 UTC; bobku
Author: Robert Kubinec [aut, cre],
  Jonah Gabry [ctb],
  Ben Goodrich [ctb],
  Trustees of Columbia University [cph]
Maintainer: Robert Kubinec <rmk7xy@virginia.edu>
Repository: CRAN
Date/Publication: 2018-02-09 11:16:51 UTC
Built: R 3.3.3; x86_64-w64-mingw32; 2018-04-22 17:51:36 UTC; windows
Archs: i386, x64
