{ "_id": "6a101ee8acfb0bcc41c8ae4b", "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\")),\nperson(\"John\",\"Walden\",role=\"aut\"))", "VignetteBuilder": "knitr", "Description": "R implementation of Quantile Data Envelopment Analysis.\nThe package 'qDEA' allows a user specified proportion of\nobservations to lie external to a given Decision Making Units's\n(DMU's)reference hyperplane. 'qDEA' can be used to detect and\naddress influential outliers or to implement quantile\nbenchmarking, as discussed in Atwood and Shaik (2020). Quantile\nbenchmarking is accomplished by using heuristic procedures to\nfind a DMU's closest input-output projection point in a\nspecified direction while allowing a specified proportion of\nobservations to lie external to the projected point's\nhyperplane. The 'qDEA' package accommodates standard (DEA) and\nquantile DEA estimation, returns to scale\nCRS(constant),VRS(variable),DRS(decreasing) or IRS(increasing),\nthe use of directional vectors, bias correction through\nsubsample bootstrapping and subsample size selection\nprocedures. The user can also recover each DMU's reference DMUs\nand external DMUs if desired. The implemented procedures are\nbased on discussions in: Atwood and Shaik (2020)\n Atwood and Shaik (2018)\n Walden and Atwood (2023)\n Walden and Atwood (2025)\n.", "License": "GPL-2 | GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-14 07:05:38 UTC", "User": "root" }, "Author": "Joe Atwood [aut, cre], John Walden [aut]", "Maintainer": "Joe Atwood ", "Config/pak/sysreqs": "cmake libicu-dev pkg-config", "Repository": "https://uaeja.r-universe.dev", "Date/Publication": "2026-04-13 15:51:02 UTC", "RemoteUrl": "https://github.com/cran/qDEA", "RemoteRef": "HEAD", "RemoteSha": "5622d94de241d622e28c6caa9e77d5f6d55a034f", "MD5sum": "3330449e623cf8d40ff3c3435bd5c83c", "_user": "uaeja", "_type": "src", "_file": "qDEA_1.0.0.tar.gz", "_fileid": "17796cfd48d463d4f3e79e3cae22ede5516838325140b9076e4c09ecd7cf17e1", "_filesize": 385259, "_sha256": "17796cfd48d463d4f3e79e3cae22ede5516838325140b9076e4c09ecd7cf17e1", 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"qDEA", "qDEA_mlist", "qDEA_solve", "qDEAbuild", "rbindSM", "SM2A", "SM2SM", "sort_list", "Write.LP" ], "_datasets": [ { "name": "CST11", "title": "Cooper,Seiford,Tone 2006 One Input One Output Example Data", "object": "CST11", "class": [ "data.frame" ], "fields": [ "STORE", "EMPLOYEES", "SALES", "SALES_EJOR", "SALES_EJOR_APDX" ], "rows": 8, "table": true, "tojson": true }, { "name": "CST12", "title": "Cooper,Seiford,Tone 2006 One Input Two Output Example Data Table 1.4", "object": "CST12", "class": [ "data.frame" ], "fields": [ "STORE", "EMPLOYEES", "CUSTOMERS", "SALES" ], "rows": 7, "table": true, "tojson": true }, { "name": "CST21", "title": "Cooper,Seiford,Tone 2006 Two Input One Output Example Table 1.3", "object": "CST21", "class": [ "data.frame" ], "fields": [ "STORE", "EMPLOYEES", "FLOOR_AREA", "SALES" ], "rows": 9, "table": true, "tojson": true }, { "name": "CST22", "title": "Cooper,Seiford,Tone 2006 Two Input Two Output Example Data Table 1.5", "object": "CST22", "class": [ "data.frame" ], "fields": [ "HOSPITAL", "DOCTORS", "NURSES", "OUT_PATIENTS", "IN_PATIENTS" ], "rows": 12, "table": true, "tojson": true } ], "_help": [ { "page": "A2SM", "title": "A2SM: Convert a matrix A to sparse matrix object ASM", "topics": [ "A2SM" ] }, { "page": "cbindSM", "title": "cbindSM: \"column bind\" two sparse matrices", "topics": [ "cbindSM" ] }, { "page": "CST11", "title": "Cooper,Seiford,Tone 2006 One Input One Output Example Data", "topics": [ "CST11" ] }, { "page": "CST12", "title": "Cooper,Seiford,Tone 2006 One Input Two Output Example Data Table 1.4", "topics": [ "CST12" ] }, { "page": "CST21", "title": "Cooper,Seiford,Tone 2006 Two Input One Output Example Table 1.3", "topics": [ "CST21" ] }, { "page": "CST22", "title": "Cooper,Seiford,Tone 2006 Two Input Two Output Example Data Table 1.5", "topics": [ "CST22" ] }, { "page": "DEAbuild", "title": "DEAbuild: Builds DDEA LP object for use in qDEA_solve function", "topics": [ "DEAbuild" ] }, { "page": "iter_delete", "title": "iter_delete: Function used for 'peeling' that supplements or supplants qDEA 'slicing' procedure. Intended to be called from qDEA function", "topics": [ "iter_delete" ] }, { "page": "lagMat", "title": "lagMat: Create a matrix of lags", "topics": [ "lagMat" ] }, { "page": "LP_highs", "title": "LP_highs Function to solve sparse LP problem using highs package", "topics": [ "LP_highs" ] }, { "page": "LPSOLVER", "title": "LPSOLVER Function to call specified solver to sparse LP problem", "topics": [ "LPSOLVER" ] }, { "page": "merge_lists", "title": "merge_lists: Merges two list objects. This function appends any objects in list2 and not in list 1 to list1 with priority given to list 1 components.", "topics": [ "merge_lists" ] }, { "page": "my_lag", "title": "my_lag: Lag a vector of values", "topics": [ "my_lag" ] }, { "page": "my_seconds", "title": "my_seconds: Function to pull seconds from proc.time function", "topics": [ "my_seconds" ] }, { "page": "nCm_mpick", "title": "nCM_mpick: Select subsample size m from mlist !!!!Intended to be called from qDEA function!!!!", "topics": [ "nCm_mpick" ] }, { "page": "qDEA", "title": "qDEA: Calling function for set of DEA and qDEA processes", "topics": [ "qDEA" ] }, { "page": "qDEA_mlist", "title": "qDEA_mlist: Obtain subsample qDEA results for a set (vector) of subsample sizes !!!Intended to be called from qDEA function!!!!", "topics": [ "qDEA_mlist" ] }, { "page": "qDEA_solve", "title": "qDEA_solve: Sets up LP objects and solves DDEA dual DEA and qDEA using highs !!!! Intended to be called from qDEA function.!!!! 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