Package: qDEA
Type: Package
Title: Quantile Data Envelopment Analysis
Version: 1.0.0
Authors@R: c(person("Joe", "Atwood", email = "jatwood@montana.edu",role = c("aut", "cre")),
             person("John","Walden",role="aut")) 
Depends: R (>= 4.2)
Imports: dplyr, doBy, highs, Matrix, utils
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Description: 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>.
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-04-07 21:56:40 UTC; h22v519
Author: Joe Atwood [aut, cre],
  John Walden [aut]
Maintainer: Joe Atwood <jatwood@montana.edu>
Repository: CRAN
Date/Publication: 2026-04-13 14:40:07 UTC
Built: R 4.6.0; ; 2026-04-25 14:02:23 UTC; unix
