NEWS.md

smfa v1.0.1: Come on, come

• 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.Rmd code examples to execute dynamically via knitr rather than using static mock outputs.

smfa v1.0.0: Imitation is the sincerest form of flattery

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)
• 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.