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PEAXAI  

Probabilistic Efficiency Analysis Using Explainable Artificial Intelligence
View on CRAN: Click here


Download and install PEAXAI package within the R console
Install from CRAN:
install.packages("PEAXAI")

Install from Github:
library("remotes")
install_github("cran/PEAXAI")

Install by package version:
library("remotes")
install_version("PEAXAI", "1.0.3")



Attach the package and use:
library("PEAXAI")
Maintained by
Ricardo González Moyano
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2025-12-02
Latest Update: 2025-12-02
Description:
Provides a probabilistic framework that integrates Data Envelopment Analysis (DEA) (Banker et al., 1984) <doi:10.1287/mnsc.30.9.1078> with machine learning classifiers (Kuhn, 2008) <doi:10.18637/jss.v028.i05> to estimate both the (in)efficiency status and the probability of efficiency for decision-making units. The approach trains predictive models on DEA-derived efficiency labels (Charnes et al., 1985) <doi:10.1016/0304-4076(85)90133-2>, enabling explainable artificial intelligence (XAI) workflows with global and local interpretability tools, including permutation importance (Molnar et al., 2018) <doi:10.21105/joss.00786>, Shapley value explanations (Strumbelj & Kononenko, 2014) <doi:10.1007/s10115-013-0679-x>, and sensitivity analysis (Cortez, 2011) <https://CRAN.R-project.org/package=rminer>. The framework also supports probability-threshold peer selection and counterfactual improvement recommendations for benchmarking and policy evaluation. The probabilistic efficiency framework is detailed in González-Moyano et al. (2025) "Probability-based Technical Efficiency Analysis through Machine Learning", in review for publication.
How to cite:
Ricardo González Moyano (2025). PEAXAI: Probabilistic Efficiency Analysis Using Explainable Artificial Intelligence. R package version 1.0.3, https://cran.r-project.org/web/packages/PEAXAI. Accessed 24 Oct. 2026.
Previous versions and publish date:
(2026-08-23 12:41), 0.1.0 (2025-12-02 15:50), 1.0.0 (2026-01-07 21:00), 1.0.1 (2026-05-19 12:40), 1.0.2 (2026-06-01 20:20)
Other packages that cited PEAXAI R package
View PEAXAI citation profile
Other R packages that PEAXAI depends, imports, suggests or enhances
Complete documentation for PEAXAI
Functions, R codes and Examples using the PEAXAI R package
Full PEAXAI package functions and examples
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