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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.

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.