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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: |
0.1.4 |
| Depends: |
R (≥ 2.10) |
| Imports: |
dplyr, conflicted, stats, ggplot2, ggparty, partykit, ggrepel, Rdpack, lpSolveAPI, utils, reshape2 |
| Suggests: |
rmarkdown, testthat, knitr, kableExtra, devtools |
| Published: |
2023-01-10 |
| DOI: |
10.32614/CRAN.package.eat |
| Author: |
Miriam Esteve 
[cre, aut],
Víctor España
[aut],
Juan Aparicio
[aut],
Xavier Barber
[aut] |
| Maintainer: |
Miriam Esteve <mestevecampello at gmail.com> |
| 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:
Downloads:
Linking:
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https://CRAN.R-project.org/package=eat
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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