Movatterモバイル変換


[0]ホーム

URL:


npsf: Nonparametric and Stochastic Efficiency and ProductivityAnalysis

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.

Version:0.8.0
Depends:Formula
LinkingTo:Rcpp
Suggests:snowFT,Rmpi
Published:2020-11-22
DOI:10.32614/CRAN.package.npsf
Author:Oleg Badunenko [aut, cre], Pavlo Mozharovskyi [aut], Yaryna Kolomiytseva [aut]
Maintainer:Oleg Badunenko <oleg.badunenko at brunel.ac.uk>
License:GPL-2
NeedsCompilation:yes
Materials:ChangeLog
CRAN checks:npsf results

Documentation:

Reference manual:npsf.html ,npsf.pdf

Downloads:

Package source: npsf_0.8.0.tar.gz
Windows binaries: r-devel:npsf_0.8.0.zip, r-release:npsf_0.8.0.zip, r-oldrel:npsf_0.8.0.zip
macOS binaries: r-release (arm64):npsf_0.8.0.tgz, r-oldrel (arm64):npsf_0.8.0.tgz, r-release (x86_64):npsf_0.8.0.tgz, r-oldrel (x86_64):npsf_0.8.0.tgz
Old sources: npsf archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=npsfto link to this page.


[8]ページ先頭

©2009-2025 Movatter.jp