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sfaR

Stochastic Frontier Analysis Routines

v1.0.1 · Oct 29, 2024 · GPL (>= 3)

Description

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.

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13 OK
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r-devel-linux-x86_64-debian-clang OK
r-devel-linux-x86_64-debian-gcc OK
r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-windows-x86_64 OK
r-oldrel-macos-arm64 OK
r-oldrel-macos-x86_64 OK
r-oldrel-windows-x86_64 OK
r-patched-linux-x86_64 OK
r-release-linux-x86_64 OK
r-release-macos-arm64 OK
r-release-macos-x86_64 OK
r-release-windows-x86_64 OK

Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Reverse Dependencies (3)

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Dependency Network

Dependencies Reverse dependencies cubature fastGHQuad Formula marqLevAlg maxLik mnorm nleqslv plm qrng randtoolbox sandwich texreg trustOptim ucminf smfa micEconDistRay metafrontier sfaR

Version History

new 1.0.1 Mar 10, 2026
updated 1.0.1 ← 1.0.0 diff Oct 28, 2024
updated 1.0.0 ← 0.1.1 diff Jul 3, 2023
updated 0.1.1 ← 0.1.0 diff May 4, 2022
updated 0.1.0 ← 0.0.91 diff May 3, 2021
new 0.0.91 Mar 4, 2021