Package: sfaR
Version: 0.1.1
Date: 2022-05-04
Title: Stochastic Frontier Analysis using R
Authors@R: c(
   person("K Hervé", "Dakpo", email = "k-herve.dakpo@inrae.fr", role = "aut"),
   person("Yann", "Desjeux", email = "yann.desjeux@inrae.fr", role = c("aut","cre")),
   person("Laure", "Latruffe", role = "aut"))
Maintainer: Yann Desjeux <yann.desjeux@inrae.fr>
Description: Maximum likelihood estimation for stochastic frontier analysis (SFA) of production 
    (profit) and cost functions. 
    The package includes several distributions for the one-sided error term (i.e. Rayleigh, 
    Gamma, Weibull, lognormal, uniform, generalized exponential and truncated skewed Laplace) 
    as well as the latent class stochastic frontier model (LCM) as described in Dakpo et al. (2021) 
 <doi:10.1111/1477-9552.12422>. 
    Several possibilities in terms of optimization algorithms are proposed. 
Depends: R (>= 3.5.0)
BugReports: https://r-forge.r-project.org/tracker/?group_id=2413
Imports: dplyr, emdbook, fBasics, Formula, gsl, marqLevAlg, MASS,
        maxLik, methods, moments, nleqslv, numDeriv, primes, qrng,
        randtoolbox, trustOptim, ucminf
Suggests: mlogit
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2022-05-05 09:52:51 UTC; ydesjeux
Author: K Hervé Dakpo [aut],
  Yann Desjeux [aut, cre],
  Laure Latruffe [aut]
Repository: CRAN
Date/Publication: 2022-05-05 14:40:02 UTC
Built: R 4.2.0; ; 2022-05-11 03:12:16 UTC; unix
