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Maximum likelihood estimation for stochastic frontier analysis (SFA) of production (profit) and cost functions. The package includes the basic stochastic frontier for cross-sectional or pooled data with several distributions for the one-sided error term (i.e., Rayleigh, gamma, Weibull, lognormal, uniform, generalized exponential and truncated skewed Laplace), the latent class stochastic frontier model (LCM) as described in Dakpo et al. (2021) <doi:10.1111/1477-9552.12422>, for cross-sectional and pooled data, and the sample selection model as described in Greene (2010) <doi:10.1007/s11123-009-0159-1>, and applied in Dakpo et al. (2021) <doi:10.1111/agec.12683>. Several possibilities in terms of optimization algorithms are proposed.
| Version: | 1.0.1 |
| Depends: | R (≥ 3.5.0) |
| Imports: | cubature, fastGHQuad, Formula, marqLevAlg, maxLik, methods, mnorm, nleqslv, plm, qrng, randtoolbox, sandwich, stats, texreg, trustOptim, ucminf |
| Suggests: | lmtest |
| Published: | 2024-10-29 |
| DOI: | 10.32614/CRAN.package.sfaR |
| Author: | K Hervé Dakpo [aut, cre], Yann Desjeux [aut], Arne Henningsen [aut], Laure Latruffe [aut] |
| Maintainer: | K Hervé Dakpo <k-herve.dakpo at inrae.fr> |
| BugReports: | https://github.com/hdakpo/sfaR/issues |
| License: | GPL (≥ 3) |
| URL: | https://github.com/hdakpo/sfaR |
| NeedsCompilation: | no |
| Language: | en-US |
| Citation: | sfaR citation info |
| Materials: | README NEWS |
| CRAN checks: | sfaR results |
| Reference manual: | sfaR.pdf |
| Package source: | sfaR_1.0.1.tar.gz |
| Windows binaries: | r-devel: sfaR_1.0.1.zip, r-release: sfaR_1.0.1.zip, r-oldrel: sfaR_1.0.1.zip |
| macOS binaries: | r-release (arm64): sfaR_1.0.1.tgz, r-oldrel (arm64): sfaR_1.0.1.tgz, r-release (x86_64): sfaR_1.0.1.tgz, r-oldrel (x86_64): sfaR_1.0.1.tgz |
| Old sources: | sfaR archive |
| Reverse imports: | micEconDistRay |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.