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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "npsf" in publications use:'
type: software
license: GPL-2.0-only
title: 'npsf: Nonparametric and Stochastic Efficiency and Productivity Analysis'
version: 0.8.0
doi: 10.32614/CRAN.package.npsf
abstract: Nonparametric efficiency measurement and statistical inference via DEA type
  estimators (see Färe, Grosskopf, and Lovell (1994) <https://doi.org/10.1017/CBO9780511551710>,
  Kneip, Simar, and Wilson (2008) <https://doi.org/10.1017/S0266466608080651> and
  Badunenko and Mozharovskyi (2020) <https://doi.org/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) <https://doi.org/10.1017/CBO9781139174411>,
  Badunenko and Kumbhakar (2016) <https://doi.org/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.
authors:
- family-names: Badunenko
  given-names: Oleg
  email: oleg.badunenko@brunel.ac.uk
- family-names: Mozharovskyi
  given-names: Pavlo
- family-names: Kolomiytseva
  given-names: Yaryna
repository: https://CRAN.R-project.org/package=npsf
date-released: '2020-11-22'
contact:
- family-names: Badunenko
  given-names: Oleg
  email: oleg.badunenko@brunel.ac.uk