eat: Efficiency Analysis Trees

Functions are provided to determine production frontiers and technical efficiency measures through non-parametric techniques based upon regression trees. The package includes code for estimating radial input, output, directional and additive measures, plotting graphical representations of the scores and the production frontiers by means of trees, and determining rankings of importance of input variables in the analysis. Additionally, an adaptation of Random Forest by a set of individual Efficiency Analysis Trees for estimating technical efficiency is also included. More details in: <doi:10.1016/j.eswa.2020.113783>.

Version: 0.1.0
Depends: R (≥ 2.10)
Imports: dplyr, conflicted, stats, knitr, ggplot2, ggparty, partykit, ggrepel, Rdpack, lpSolveAPI, utils, reshape2
Suggests: rmarkdown, testthat, kableExtra, usethis, devtools
Published: 2021-04-09
Author: Miriam Esteve ORCID iD [cre, aut], Víctor España [aut], Juan Aparicio ORCID iD [aut], Xavier Barber ORCID iD [aut]
Maintainer: Miriam Esteve <miriam.estevec at umh.es>
BugReports: https://github.com/MiriamEsteve/EAT/issues
License: GPL-3
URL: https://efficiencytools.wordpress.com/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: eat results

Documentation:

Reference manual: eat.pdf
Vignettes: EAT: Efficiency Analysis Trees

Downloads:

Package source: eat_0.1.0.tar.gz
Windows binaries: r-devel: eat_0.1.0.zip, r-release: eat_0.1.0.zip, r-oldrel: eat_0.1.0.zip
macOS binaries: r-release (arm64): eat_0.1.0.tgz, r-release (x86_64): eat_0.1.0.tgz, r-oldrel: eat_0.1.0.tgz

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