Package: sfaR
Title: Stochastic Frontier Analysis Routines
Version: 1.0.0
Authors@R: c(
    person("K Hervé", "Dakpo", email = "k-herve.dakpo@inrae.fr", role = c("aut", "cre")),
    person("Yann", "Desjeux", role = "aut"),
    person("Arne", "Henningsen", role = "aut"),
    person("Laure", "Latruffe", role = "aut")
  )
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.
License: GPL (>= 3)
URL: https://github.com/hdakpo/sfaR
BugReports: https://github.com/hdakpo/sfaR/issues
Depends: 
    R (>= 3.5.0)
Imports: 
    cubature,
    fastGHQuad,
    Formula,
    marqLevAlg,
    maxLik,
    methods,
    mnorm,
    nleqslv,
    plm,
    qrng,
    randtoolbox,
    sandwich,
    stats,
    texreg,
    trustOptim,
    ucminf
Suggests: 
    lmtest
Encoding: UTF-8
Language: en-US
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
