boostingDEA: A Boosting Approach to Data Envelopment Analysis

Includes functions to estimate production frontiers and make ideal output predictions in the Data Envelopment Analysis (DEA) context using both standard models from DEA and Free Disposal Hull (FDH) and boosting techniques. In particular, EATBoosting (Guillen et al., 2023 <doi:10.1016/j.eswa.2022.119134>) and MARSBoosting. Moreover, the package includes code for estimating several technical efficiency measures using different models such as the input and output-oriented radial measures, the input and output-oriented Russell measures, the Directional Distance Function (DDF), the Weighted Additive Measure (WAM) and the Slacks-Based Measure (SBM).

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: Rglpk, dplyr, lpSolveAPI, stats, MLmetrics, methods
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2023-05-15
DOI: 10.32614/CRAN.package.boostingDEA
Author: Maria D. Guillen ORCID iD [cre, aut], Juan Aparicio ORCID iD [aut], Víctor España ORCID iD [aut]
Maintainer: Maria D. Guillen <maria.guilleng at>
License: AGPL (≥ 3)
NeedsCompilation: no
Materials: README
CRAN checks: boostingDEA results


Reference manual: boostingDEA.pdf
Vignettes: boostingDEA


Package source: boostingDEA_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): boostingDEA_0.1.0.tgz, r-oldrel (arm64): boostingDEA_0.1.0.tgz, r-release (x86_64): boostingDEA_0.1.0.tgz, r-oldrel (x86_64): boostingDEA_0.1.0.tgz


Please use the canonical form to link to this page.