sfaR

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) , for cross-sectional and pooled data, and the sample selection model as described in Greene (2010) , and applied in Dakpo et al. (2021) . Several possibilities in terms of optimization algorithms are proposed.

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