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This provides a robust estimator for stochastic frontier models, employing the Minimum Density Power Divergence Estimator (MDPDE) for enhanced robustness against outliers. Additionally, it includes a function to recommend the optimal tuning parameter, alpha, which controls the robustness of the MDPDE. The methods implemented in this package are based on Song et al. (2017) <doi:10.1016/j.csda.2016.08.005>.
| Version: | 0.2.0 |
| Imports: | stats, truncnorm, Rcpp, frontier |
| LinkingTo: | Rcpp, BH |
| Published: | 2025-03-21 |
| DOI: | 10.32614/CRAN.package.robustSFA |
| Author: | Junmo Song [aut, cre], Dong-hyun Oh [aut] |
| Maintainer: | Junmo Song <junmo.song at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | robustSFA results |
| Reference manual: | robustSFA.pdf |
| Package source: | robustSFA_0.2.0.tar.gz |
| Windows binaries: | r-devel: robustSFA_0.2.0.zip, r-release: robustSFA_0.2.0.zip, r-oldrel: robustSFA_0.2.0.zip |
| macOS binaries: | r-devel (arm64): robustSFA_0.2.0.tgz, r-release (arm64): robustSFA_0.2.0.tgz, r-oldrel (arm64): robustSFA_0.2.0.tgz, r-devel (x86_64): robustSFA_0.2.0.tgz, r-release (x86_64): robustSFA_0.2.0.tgz, r-oldrel (x86_64): robustSFA_0.2.0.tgz |
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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.