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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.

Versions across snapshots

VersionRepositoryFileSize
1.0.1 rolling linux/jammy R-4.5 sfaR_1.0.1.tar.gz 2.8 MiB
1.0.1 rolling linux/noble R-4.5 sfaR_1.0.1.tar.gz 2.8 MiB
1.0.1 rolling source/ R- sfaR_1.0.1.tar.gz 667.5 KiB
1.0.1 latest linux/jammy R-4.5 sfaR_1.0.1.tar.gz 2.8 MiB
1.0.1 latest linux/noble R-4.5 sfaR_1.0.1.tar.gz 2.8 MiB
1.0.1 latest source/ R- sfaR_1.0.1.tar.gz 667.5 KiB
1.0.1 2026-04-26 source/ R- sfaR_1.0.1.tar.gz 667.5 KiB
1.0.1 2026-04-23 source/ R- sfaR_1.0.1.tar.gz 667.5 KiB
1.0.1 2026-04-09 windows/windows R-4.5 sfaR_1.0.1.zip 2.8 MiB
1.0.1 2025-04-20 source/ R- sfaR_1.0.1.tar.gz 667.5 KiB

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