Quantile Data Envelopment Analysis
Overview
R implementation of Quantile Data Envelopment Analysis. The package 'qDEA' allows a user specified proportion of observations to lie external to a given Decision Making Units's (DMU's)reference hyperplane. 'qDEA' can be used to detect and address influential outliers or to implement quantile benchmarking, as discussed in Atwood and Shaik (2020). Quantile benchmarking is accomplished by using heuristic procedures to find a DMU's closest input-output projection point in a specified direction while allowing a specified proportion of observations to lie external to the projected point's hyperplane. The 'qDEA' package accommodates standard (DEA) and quantile DEA estimation, returns to scale CRS(constant),VRS(variable),DRS(decreasing) or IRS(increasing), the use of directional vectors, bias correction through subsample bootstrapping and subsample size selection procedures. The user can also recover each DMU's reference DMUs and external DMUs if desired. The implemented procedures are based on discussions in: Atwood and Shaik (2020) doi:10.1016/j.ejor.2020.03.054 Atwood and Shaik (2018) doi:10.1007/978-3-319-68678-3_4 Walden and Atwood (2023) doi:10.1086/724932 Walden and Atwood (2025) doi:10.1086/736554.
Initial CRAN Release
- First public release of qDEA package
- Implements quantile Data Envelopment Analysis methods
- Main function
qDEA()for efficiency analysis with multiple orientations - Support for various returns to scale specifications (CRS, VRS, DRS, IRS)
- Bootstrap bias correction procedures
- Subsample size selection following Simar and Wilson (2011)
- Helper functions for DEA model building and LP solving
- Four example datasets from Cooper, Seiford, and Tone (2006)
- Integration with highs solver for linear programming
Key Features
- Standard DEA and quantile DEA (qDEA) estimation
Show all changes in 1.0.0Hide the rest of the changes in 1.0.0
- Multiple model orientations: input, output, graph, hyperbolic, and directional distance
- Iterative qDEA with convergence testing
- Bootstrap-based bias correction
- Peer identification and projection calculations
- Comprehensive documentation with examples
From NEWS.md in the release
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK5 OK2026-04-14
Documentation
- Help pages
- 24
- Examples that run
- 100%5 run in a plain check
- Exported functions with examples
- 26%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Dependencies
Code & Tests
Datasets
People & History
- RR 4.6.0 released · 2026-04-24
- 1.0.0Latest2026-04-13 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2026-04-13
- Total releases
- 1 / 1 yrs
- License
- GPL-2 | GPL-3 OSI
- Minimum R
- ≥ 4.2
- Bundled data
- 1.0 KB / 4 files
- Download size
- 105 KB
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