npsf
Nonparametric and Stochastic Efficiency and Productivity Analysis
Nonparametric efficiency measurement and statistical inference via DEA type estimators (see Färe, Grosskopf, and Lovell (1994) <doi:10.1017/CBO9780511551710>, Kneip, Simar, and Wilson (2008) <doi:10.1017/S0266466608080651> and Badunenko and Mozharovskyi (2020) <doi:10.1080/01605682.2019.1599778>) as well as Stochastic Frontier estimators for both cross-sectional data and 1st, 2nd, and 4th generation models for panel data (see Kumbhakar and Lovell (2003) <doi:10.1017/CBO9781139174411>, Badunenko and Kumbhakar (2016) <doi:10.1016/j.ejor.2016.04.049>). The stochastic frontier estimators can handle both half-normal and truncated normal models with conditional mean and heteroskedasticity. The marginal effects of determinants can be obtained.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.8.0 |
rolling linux/jammy R-4.5 | npsf_0.8.0.tar.gz |
1.1 MiB |
0.8.0 |
rolling linux/noble R-4.5 | npsf_0.8.0.tar.gz |
1.1 MiB |
0.8.0 |
rolling source/ R- | npsf_0.8.0.tar.gz |
952.2 KiB |
0.8.0 |
latest linux/jammy R-4.5 | npsf_0.8.0.tar.gz |
1.1 MiB |
0.8.0 |
latest linux/noble R-4.5 | npsf_0.8.0.tar.gz |
1.1 MiB |
0.8.0 |
latest source/ R- | npsf_0.8.0.tar.gz |
952.2 KiB |
0.8.0 |
2026-04-26 source/ R- | npsf_0.8.0.tar.gz |
952.2 KiB |
0.8.0 |
2026-04-23 source/ R- | npsf_0.8.0.tar.gz |
952.2 KiB |
0.8.0 |
2026-04-09 windows/windows R-4.5 | npsf_0.8.0.zip |
1.4 MiB |
0.8.0 |
2025-04-20 source/ R- | npsf_0.8.0.tar.gz |
952.2 KiB |