SemiParBIVProbit: Semiparametric Bivariate Probit Modelling

Routine for fitting bivariate probit models with semiparametric predictors (including linear and nonlinear effects) in the presence of correlated error equations, endogeneity or sample selection. Bivariate copula models are also supported.

Version: 3.2-10
Depends: R (≥ 2.14.0), CDVine (≥ 1.1-13), VGAM (≥ 0.9-2), mgcv (≥ 1.7-26), mvtnorm (≥ 0.9-9996)
Imports: MASS, magic, polycor, VineCopula, survey, trust, matrixStats, Matrix
Published: 2014-02-14
Author: Giampiero Marra and Rosalba Radice
Maintainer: Giampiero Marra <giampiero.marra at ucl.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www.ucl.ac.uk/statistics/people/giampieromarra
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: SemiParBIVProbit results

Downloads:

Reference manual: SemiParBIVProbit.pdf
Package source: SemiParBIVProbit_3.2-10.tar.gz
OS X binary: SemiParBIVProbit_3.2-10.tgz
Windows binary: SemiParBIVProbit_3.2-10.zip
Old sources: SemiParBIVProbit archive