sfaR: Stochastic Frontier Analysis Routines

Maximum likelihood estimation for stochastic frontier analysis (SFA) of production (profit) and cost functions. The package includes the basic stochastic frontier for cross-sectional or pooled data with several distributions for the one-sided error term (i.e., Rayleigh, gamma, Weibull, lognormal, uniform, generalized exponential and truncated skewed Laplace), the latent class stochastic frontier model (LCM) as described in Dakpo et al. (2021) <doi:10.1111/1477-9552.12422>, for cross-sectional and pooled data, and the sample selection model as described in Greene (2010) <doi:10.1007/s11123-009-0159-1>, and applied in Dakpo et al. (2021) <doi:10.1111/agec.12683>. Several possibilities in terms of optimization algorithms are proposed.

Version: 1.0.0
Depends: R (≥ 3.5.0)
Imports: cubature, fastGHQuad, Formula, marqLevAlg, maxLik, methods, mnorm, nleqslv, plm, qrng, randtoolbox, sandwich, stats, texreg, trustOptim, ucminf
Suggests: lmtest
Published: 2023-07-04
Author: K Hervé Dakpo [aut, cre], Yann Desjeux [aut], Arne Henningsen [aut], Laure Latruffe [aut]
Maintainer: K Hervé Dakpo <k-herve.dakpo at inrae.fr>
BugReports: https://github.com/hdakpo/sfaR/issues
License: GPL (≥ 3)
URL: https://github.com/hdakpo/sfaR
NeedsCompilation: no
Language: en-US
Citation: sfaR citation info
Materials: README NEWS
CRAN checks: sfaR results


Reference manual: sfaR.pdf


Package source: sfaR_1.0.0.tar.gz
Windows binaries: r-devel: sfaR_1.0.0.zip, r-release: sfaR_1.0.0.zip, r-oldrel: sfaR_1.0.0.zip
macOS binaries: r-release (arm64): sfaR_1.0.0.tgz, r-oldrel (arm64): sfaR_1.0.0.tgz, r-release (x86_64): sfaR_1.0.0.tgz, r-oldrel (x86_64): sfaR_0.1.1.tgz
Old sources: sfaR archive

Reverse dependencies:

Reverse imports: micEconDistRay
Reverse suggests: dsfa


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