Semiparametric Bivariate Probit Modelling Routine for fitting bivariate probit models with semiparametric predictors (including linear, nonlinear and nonparametric random effects) in the presence of correlated error equations, endogeneity or sample selection. Software Depends: R (>= 2.14.0), MASS, VGAM, magic, statmod, mgcv, trust, mvtnorm Giampiero Marra <giampiero@stats.ucl.ac.uk> Giampiero Marra <giampiero@stats.ucl.ac.uk> and Rosalba Radice <rosalba.radice@lshtm.ac.uk> with contributions from Georgios Papageorgiou <gpapageo@gmail.com> GPL (>= 2) 2012-05-16 application/tgz http://CRAN.R-project.org/package=SemiParBIVProbit