Package: npsf
Type: Package
Title: Nonparametric and Stochastic Efficiency and Productivity
        Analysis
Version: 0.8.0
Date: 2020-11-22
Author: Oleg Badunenko [aut, cre], Pavlo Mozharovskyi [aut], Yaryna
        Kolomiytseva [aut]
Maintainer: Oleg Badunenko <oleg.badunenko@brunel.ac.uk>
Description: Nonparametric efficiency measurement and statistical
        inference via DEA type estimators (see Färe, Grosskopf, and
        Lovell (1994) <doi:10.1017/CBO9780511551710>, Kneip, Simar, and
        Wilson (2008) <doi:10.1017/S0266466608080651> and Badunenko and
        Mozharovskyi (2020) <doi:10.1080/01605682.2019.1599778>) as
        well as Stochastic Frontier estimators for both cross-sectional
        data and 1st, 2nd, and 4th generation models for panel data
        (see Kumbhakar and Lovell (2003)
        <doi:10.1017/CBO9781139174411>, Badunenko and Kumbhakar (2016)
        <doi:10.1016/j.ejor.2016.04.049>). The stochastic frontier
        estimators can handle both half-normal and truncated normal
        models with conditional mean and heteroskedasticity. The
        marginal effects of determinants can be obtained.
Depends: Formula
Suggests: snowFT, Rmpi
Encoding: UTF-8
License: GPL-2
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-06-23 16:48:30 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2020-11-22 21:10:02 UTC
RemoteUrl: https://github.com/cran/npsf
RemoteRef: HEAD
RemoteSha: 87861539a705a43a1f5e2cb66e80cf45c715f266