smfa v1.0.1
- Updated the reference for the generalised exponential distribution to Papadopoulos (2021) in the documentation.
- Fixed duplicated citation of Papadopoulos (2015) in documentation.
- Added comprehensive, CRAN-compliant unit tests via
testthat. - Fixed missing alt text for badges in README files.
- Refactored
README.Rmdcode examples to execute dynamically viaknitrrather than using static mock outputs.
smfa v1.0.0: Imitation is the sincerest form of flattery
CRAN release: 2026-04-28
The definitive, original implementation of stochastic metafrontier analysis for R is officially stable.
After rigorous development, extensive methodological testing, and refinement for CRAN submission, smfa v1.0.0 provides a robust, production-ready environment for productivity and performance benchmarking across firms operating under different technologies. This release establishes the standard for stochastic metafrontier analysis in the R ecosystem.
Initial CRAN release
- First public release of
smfa. - Implements stochastic metafrontier analysis for productivity and performance benchmarking across firms operating under different technologies.
- Supports three group-frontier types via ‘sfaR’:
- Standard SFA (
sfacross) - Latent class SFA (
sfalcmcross) - Sample-selection-corrected SFA (
sfaselectioncross)
- Standard SFA (
- Three metafrontier estimation methods:
- Linear programming (LP) deterministic envelope
- Quadratic programming (QP) deterministic envelope
- Second-stage stochastic frontier (Huang et al. 2014; O’Donnell et al. 2008)
- Full efficiency outputs via
efficiencies(): group TE (JLMS and BC), metafrontier TE, and metatechnology ratios (MTR). - Five vignettes illustrating each major use case.