Package: BiProbitPartial
Type: Package
Title: Bivariate Probit with Partial Observability
Version: 1.0.3
Date: 2019-01-10
Author: Michael Guggisberg and Amrit Romana
Maintainer: Michael Guggisberg <mguggisb@ida.org>
Description: A suite of functions to estimate, summarize
  and perform predictions with the bivariate probit subject to partial observability.
  The frequentist and Bayesian probabilistic philosophies are both supported. The 
  frequentist method is estimated with maximum likelihood and the Bayesian method is 
  estimated with a Markov Chain Monte Carlo (MCMC) algorithm developed by 
  Rajbanhdari, A (2014) <doi:10.1002/9781118771051.ch13>.
License: GPL-3
Imports: Rcpp(>= 0.12.19), Formula(>= 1.2-3), optimr(>= 2016-8.16),
        pbivnorm(>= 0.6.0), mvtnorm(>= 1.0-8), RcppTN(>= 0.2-2),
        coda(>= 0.19-2)
Depends: numDeriv(>= 2016.8-1)
Suggests: sampleSelection
LinkingTo: Rcpp, RcppArmadillo, RcppTN
RoxygenNote: 6.1.0
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-01-10 13:55:32 UTC; mguggisb
Repository: CRAN
Date/Publication: 2019-01-10 22:12:04 UTC
Built: R 4.1.0; x86_64-w64-mingw32; 2020-08-03 06:17:11 UTC; windows
Archs: i386, x64
