Semiparametric Estimation of Stochastic Frontier Models following a two step procedure: in the first step semiparametric or nonparametric regression techniques are used to relax parametric restrictions of the functional form representing technology and in the second step variance parameters are obtained by pseudolikelihood estimators or by method of moments.
| Version: | 1.1 |
| Depends: | R (≥ 3.1.2), mgcv, np, gamlss |
| Imports: | moments, doParallel, foreach, iterators |
| Published: | 2018-04-20 |
| Author: | Giancarlo Ferrara and Francesco Vidoli |
| Maintainer: | Giancarlo Ferrara <giancarlo.ferrara at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| NeedsCompilation: | no |
| In views: | Econometrics |
| CRAN checks: | semsfa results |
| Reference manual: | semsfa.pdf |
| Package source: | semsfa_1.1.tar.gz |
| Windows binaries: | r-devel: semsfa_1.1.zip, r-release: semsfa_1.1.zip, r-oldrel: semsfa_1.1.zip |
| macOS binaries: | r-release (arm64): semsfa_1.1.tgz, r-oldrel (arm64): semsfa_1.1.tgz, r-release (x86_64): semsfa_1.1.tgz, r-oldrel (x86_64): semsfa_1.1.tgz |
| Old sources: | semsfa archive |
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