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: |
3.2-11 |
| Depends: |
R (≥ 2.14.0), CDVine (≥ 1.1-13), mgcv (≥ 1.7-26), mvtnorm (≥ 0.9-9996) |
| Imports: |
MASS, magic, polycor, VineCopula, VGAM, survey, trust, matrixStats, Matrix, sn |
| Published: |
2014-07-02 |
| 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 |