Package: smfa 1.0.1

smfa: Stochastic Metafrontier Analysis

Implements stochastic metafrontier analysis for productivity and performance benchmarking across firms operating under different technologies. Contains routines for the deterministic metafrontier envelope of O'Donnell et al. (2008) <doi:10.1007/s00181-007-0119-4> via linear and quadratic programming, and the stochastic metafrontier of Huang et al. (2014) <doi:10.1007/s11123-014-0402-2>. Also supports latent class stochastic metafrontier analysis and sample selection correction stochastic metafrontier models. Depends on the 'sfaR' package by Dakpo et al. (2023) <https://CRAN.R-project.org/package=sfaR>.

Authors:Sulman Olieko Owili [aut, cre]

smfa_1.0.1.tar.gz
smfa_1.0.1.zip(r-4.7-any)smfa_1.0.1.zip(r-4.6-any)smfa_1.0.1.zip(r-4.5-any)
smfa_1.0.1.tgz(r-4.6-any)smfa_1.0.1.tgz(r-4.5-any)
smfa_1.0.1.tar.gz(r-4.7-any)smfa_1.0.1.tar.gz(r-4.6-any)
smfa_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
smfa/json (API)

# Install 'smfa' in R:
install.packages('smfa', repos = c('https://sulmanolieko.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/sulmanolieko/smfa/issues

Pkgdown/docs site:https://sulmanolieko.github.io

On CRAN:

Conda:

5.81 score 2 stars 16 scripts 330 downloads 1 exports 46 dependencies

Last updated from:0cf20499b8. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK207
source / vignettesOK260
linux-release-x86_64OK263
macos-release-arm64OK147
macos-oldrel-arm64OK104
windows-develOK117
windows-releaseOK143
windows-oldrelOK129
wasm-releaseOK175

Exports:smfa

Dependencies:askpassbdsmatrixcodetoolscollapsecubaturecurldigestdoParallelfastGHQuadforeachFormulagenericshpahttriteratorsjsonlitelatticelmtestmarqLevAlgMASSMatrixmaxLikmimemiscToolsmnormnleqslvnlmeopensslplmqrngR6randtoolboxrbibutilsRcppRcppArmadilloRcppEigenRcppParallelRdpackrngWELLsandwichsfaRsystexregtrustOptimucminfzoo

Sample Selection SFA Metafrontier (groupType = "sfaselectioncross")
Overview | Data Preparation (Simulated Example) | Method 1: sfaselectioncross + LP Metafrontier | Method 2: sfaselectioncross + QP Metafrontier | Method 3: sfaselectioncross + SFA (Huang) | Method 4: sfaselectioncross + SFA (O'Donnell) | Interpreting the Selection Correction | Extracting Efficiencies
Rendered fromsfaselectioncross-metafrontier.Rmdusingknitr::rmarkdown

Last update: 2026-07-14
Started: 2026-03-12

Standard SFA Metafrontier (groupType = "sfacross")
Overview | Data Preparation | Method 1: LP Metafrontier | Method 2: QP Metafrontier | Method 3: Stochastic Metafrontier — Huang et al. (2014) | Method 4: Stochastic Envelope — O'Donnell et al. (2008) | Comparing Methods | Extracting Efficiencies | Other Extractors
Rendered fromsfacross-metafrontier.Rmdusingknitr::rmarkdown

Last update: 2026-07-14
Started: 2026-03-12

Extracting Efficiencies and MTRs
Overview | Setup: Fit a Model | summary() — Full Model Summary | efficiencies() — Firm-Level Efficiency and MTR Scores | Column Reference | Subsetting by Group | Visualising the Distribution | coef() — Estimated Coefficients | vcov() — Variance-Covariance Matrix | logLik() — Log-Likelihood | ic() — Information Criteria | nobs() — Number of Observations | fitted() — Fitted Values | residuals() — Residuals | Comparing Multiple Models
Rendered fromefficiency-extraction.Rmdusingknitr::rmarkdown

Last update: 2026-07-14
Started: 2026-03-12

Getting Started with smfa
What is smfa? | Conceptual Framework | Methods Supported | Installation | Quick-Start Example | Step 1: Load data and create groups | Step 2: Fit the metafrontier model | Step 3: Summarise results | Step 4: Extract firm-level efficiencies | What Next?
Rendered fromgetting-started.Rmdusingknitr::rmarkdown

Last update: 2026-07-14
Started: 2026-03-12

Latent Class SFA Metafrontier (groupType = "sfalcmcross")
Overview | Data Preparation | Method 1: LCM + LP Metafrontier | Method 2: LCM + QP Metafrontier | Method 3: LCM + SFA (Huang) | Method 4: LCM + SFA (O'Donnell) | Choosing the Number of Classes | Extracting Efficiencies and Posterior Probabilities | Class membership summary | Key Difference from sfacross
Rendered fromsfalcmcross-metafrontier.Rmdusingknitr::rmarkdown

Last update: 2026-07-14
Started: 2026-03-12