Stochastic Frontier Analysis Routines R package sfaR version 1.0.1 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. Software Depends: R (>= 3.5.0) Imports: cubature, fastGHQuad, Formula, marqLevAlg, maxLik, methods, mnorm, nleqslv, plm, qrng, randtoolbox, sandwich, stats, texreg, trustOptim, ucminf Suggests: lmtest K Hervé Dakpo <k-herve.dakpo@inrae.fr> Comprehensive R Archive Network (CRAN) K Hervé Dakpo [aut, cre], Yann Desjeux [aut], Arne Henningsen [aut], Laure Latruffe [aut] GPL (>= 3) 2024-10-29 application/tgz https://CRAN.R-project.org/package=sfaR doi:10.32614/CRAN.package.sfaR en-US