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0.7.1Package record

Data Envelopment Analysis for Pollution-Generating Technologies

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819downloads / year
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Overview

About
Maintained by Erik EnstadCRAN page ↗GitHub ↗Issues ↗

Nonparametric efficiency analysis for pollution-generating technologies under the materials-balance principle. Implements the weak-G-disposability technology of Hampf and Rodseth (2015) doi:10.1016/j.eneco.2015.04.001, scored by the minimal-emission programme of Rodseth (2025) doi:10.1007/s11123-025-00768-0 with its directional representation and five-component decomposition, the by-production intersection technology of Murty, Russell and Levkoff (2012) doi:10.1016/j.jeem.2012.02.005, the materials-balance cost model of Coelli, Lauwers and Van Huylenbroeck (2007) doi:10.1007/s11123-007-0052-8 and a weak-disposability reference model, with a pre-estimation audit of every materials-balance account, metafrontier decompositions, bad-output shadow prices, marginal abatement cost curves, a cross-axiom comparison harness, a global Malmquist-Luenberger productivity index and subsampling sensitivity intervals. Estimators are solved with 'lpSolveAPI'.

Changes in 0.7.1
  • Every LP kernel now checks the point lp_solve returns against the rows and bounds of its programme. lp_solve accepts a point once each row holds within its tolerances on its own internally scaled model, and on the unit-magnitude copy of the data a small unit's rows are of order 1e-7, where those tolerances can exceed several per cent of the row. On uscoal with the sulfur coefficients scaled by 0.9, model = "wgd_input_fixed" returned status 0 at Painesville (plant 2936, 38 MWh) with b_star 6 per cent above the cap (mb_headroom -0.39 t), although no peer mix emits less than the plant's own 6.543 t and the programme is infeasible. A row now fails when its residual exceeds 1e-5 times the largest of its right-hand side, its largest term and the unit's own pollutant level, plus 1e-7 times the total peer weight times the row's largest coefficient on a peer weight in the solution (lp_solve leaves weights of about 1e-8 on peers it does not use); a failing point is reported as infeasible (status 2) with NA scores, and a unit whose own observation is feasible is retried under the alternative lp_solve settings as before. On the shipped data no other status or score changes: across every model, both peer sets and returns to scale, the decompositions and 50 perturbations of the uscoal sulfur coefficients, the only change is Painesville's status in the 0.9 scenario and in the 13 draws where it was reported above its cap.
Show all changes in 0.7.1Hide the rest of the changes in 0.7.1
  • model = "wgd_input_fixed" now decides whether a unit meets its materials-balance caps (and so whether an infeasibility verdict is retried) on the data with the relative 1e-5. The previous test allowed an absolute 1e-8 on the unit-magnitude copy, 0.78 t of SO2 on uscoal, so it took Painesville's 0.39 t excess for a met cap, rejected lp_solve's correct verdict of infeasibility and accepted the point above the cap from the first alternative scaling.
  • Documentation: citations corrected after a check against the cited papers. No estimator changes.
  • The weak-G-disposability technology is credited to Hampf and Rodseth (2015); "wgd" scores it by the minimal-emission programme of Rodseth (2025, Eq. 6).
  • model = "fdmo" is Rodseth's Eq. 13 with abatement fixed at the DMU's own level; Eq. 14 is the equivalent convex-regression form (Proposition 4). Version 0.7.0 cited Eq. 14 for the programme.
  • The pigfarms replication (vignette and tests) uses the good-output coefficient v = 7/6 implied by farms A and B, under which "wgd" reproduces every Table 2 target of Rodseth (2025). The v = 0 mapping left farms A and B tied as peers, so the targets of farms B and C were solver-dependent; that was a property of the mapping, not of the source.
  • mean_eff of "byprod" is described as Murty, Russell and Levkoff's by-production efficiency index (one good and one bad output), not as a variant of the graph measure.
  • boot_pgt(): Kneip, Simar and Wilson (2008) prove the m-out-of-n bootstrap with replacement consistent under VRS; the default rates are credited to Kneip, Park and Simar (1998) for VRS and to Park, Jeong and Simar (2010) for CRS.
  • pgt_ml(): the global frontier removes the cross-period infeasibility (Oh 2010), not the inconsistency of Aparicio, Pastor and Zofio (2013); BPC is the best-practice gap change; the default "wd" technology reproduces Oh's constant-returns technology with returns = "crs".
  • pgt_decompose(): TGR is the technology gap ratio of Battese, Rao and O'Donnell (2004), the metatechnology ratio of O'Donnell, Rao and Battese (2008); WR is the efficiency against the group frontier.
  • A second check against the full sources: "wgd" fits the technology of Hampf and Rodseth (2015) with the minimal-emission programme of Rodseth (2025, Eq. 6), whereas Hampf and Rodseth score by a ratio of output to emission. For "fdmo", Eq. 13 is the indirect form of the directional programme of Eq. 12 under common coefficients, and the sign restrictions come from Eq. 14. "byprod" cites Murty, Russell and Levkoff (2012, Eqs. 4.5, 4.7, 5.7 and 7.1): their technology has constant returns, and their application omits the abatement output, as "byprod" does. "wgd_input_fixed" is documented as differing from weak G-disposability at fixed inputs. The uscoal help notes that about 95 per cent of fuel sulfur converts to SO2 (Rodseth 2017). The boot_pgt() and pgt_ml() help state the conditions of the cited results.
  • Numerical robustness: every solve of "wgd", "envelope", "wgd_input_fixed" and the stages of pgt_decompose(type = "rodseth") is now checked against the bound that self-reference gives. When the evaluated unit is among its peers (and, for "wgd_input_fixed", meets its own materials-balance caps), its observation is feasible and attains b, so a solve returning b* > b, or infeasibility, is a suboptimal vertex or a failed solve of lp_solve. Such a solve, and any numerical failure (status 5), is rebuilt and re-solved under two alternative lp_solve scalings and then the primal simplex, a retry the decomposition stages alone had before and only for failed solves. A unit whose every attempt still returns b* > b gets status 1 (lp_solve's SUBOPTIMAL code) and NA scores, and pgt() counts such units in its warning. A solve that passes the check at the first attempt is unchanged. On a 1,142-plant-year steel panel in tonnes, 0.7.0 reported up to three infeasible "wgd_input_fixed" programmes per specification as numerical failures (status 5); every infeasible programme now reports status 2, and every status matches an independent GLPK solve.
  • New test-scaling.R on steeldemo with every quantity multiplied by 1e6 (up to 1e13). It checks the decomposition's first stage against its reduced form, solved separately on a copy in million tonnes; "wgd", "wgd_input_fixed", "envelope" and the decomposition against a common rescaling of the quantities; "wgd_input_fixed" feasibility with and without materials-balance violators; and the retry and its status-1 report. Without the rescaling of 0.7.0, 96 of the 180 first-stage optima are suboptimal at this magnitude, two with production technical efficiency above 1, and three self-feasible "wgd_input_fixed" programmes are reported infeasible. The tests mock an internal kernel, so testthat (>= 3.1.7) is suggested.
  • model = "fdmo" adds the row theta_b <= b (projected emission non-negative). Rodseth's Eq. 14 is derived for coefficients common to all units; with producer-specific coefficients the balance row applies the evaluated unit's coefficients to a peer mix of units with other coefficients, and a unit whose inputs carry little pollutant could borrow a pollutant-rich peer's output and receive a negative projected emission (two closed accounts suffice). Under common coefficients and closed accounts the row never binds, so the pigfarms Table 3 replication and every closed-account result with common coefficients are unchanged.
  • model = "wgd": z_star now adds the retained content of the output overshoot, z_star = sum(lambda * z) + v_i'(sum(lambda * y) - y_i), so that z_star - a_star = b_star whenever the peers' accounts close. The earlier z_star was the peer mix of caps alone and did not match b_star when the optimal mix produced more than the unit with v > 0. b_star and the scores are unchanged, and so is the pigfarms Table 2 replication (v = 0).
  • compare_models() ranks scores within 1e-8 of each other as ties in the Spearman matrix and the bottom-quartile overlap. Efficient units score 1 up to solver noise (below 1e-9 on the shipped data), and ranking that noise made the correlations depend on the solver build: mb_cost-wd on uscoal was 0.221 with one 0.7.0 build and 0.247 with another. The returned scores are unrounded.
  • The Monte Carlo study inst/simulations/coverage.R now records interval availability (boot_pgt() returns NA bounds when fewer than B/2 subsample LPs are feasible, which under VRS hits the units with the largest output), reports coverage among units with an interval and the share of all units whose interval exists and covers, adds a curved frontier to the affine one and an m and kappa sensitivity at L = 100, keeps per-replication results in coverage-reps.csv, and reports Monte Carlo standard errors across replications.
  • Documentation: the unit dependence of the "fdmo" gross score ends at the reported sum. The balance row fixes theta_b given theta_y, so the programme maximises theta_y and a coherent change of units leaves the optimum unchanged; the earlier help text said the optimiser could change. The replication vignette no longer calls the farm E row of Rodseth's Table 3 inconsistent with a common v: the paper prints one decimal, and common coefficients within that rounding reproduce every printed row, as a new test asserts.

From NEWS.md in the release

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Health

CRAN checks
13OK
Slowest check: 3.7 min · r-oldrel-macos-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE11 OK, 1 NOTE2026-08-01
  • OK7 OK2026-07-29
Advisories

none known

How this is measured·How advisories are found

Documentation

In release 0.7.1
READMEYes · 1,026 wordsVignettesYes · 6 · evaluation depends on the environmentNEWSYes · 100% structured · mentions 0.7.1Citation fileYes · computed when R runs itWebsitenot declared in DESCRIPTION
Help pages
15 (1 internal)includes a package overview page
Examples that run
100%14 run in a plain check
Exported functions with examples
100%
Documented parameters
87%
Return-value docs
100%
Help pages citing references
60% with a bibliography file
Vignettes (6)
How these are measured

Downloads

819
CRAN downloads in the past year
Rank #14,611 · ~2/day · ~68/mo
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36430 days
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Repository

iik1/pgt ↗Account: iik1
1Stars
0Forks
0Open issues
0Open PRs
0Releases
37Commits
2Commit identities
37 commits · Last activity 2026-10-13 · 0% stars, 30d
Responsiveness
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PRs merged (all time)
100%
Median days to close, 50 most recently updated closed issues
not measured
Median days to close, 50 most recently updated closed PRs
0

Stars over time

2026-07-29 · 02026-07-31 · 1
How these are measured
PracticesBeta

5 development-tooling and community-health practices detected across 4 families in the upstream repository

Checks run against github.com/iik1/pgt on 2026-10-18.

Continuous integration (2)
GitHub ActionsR CMD check workflow

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Docs source (1)
pkgdown
Reproducibility and dev environment (1)
data-raw/
CRAN release process (1)
cran-comments.md
How this is detected·Detection ruleset v3 (2026-09-26)

Dependencies

Declared dependencies
5 external dependencies (excludes base and recommended)

Installing pgt adds 1 package (1 with compiled code, 479 KB of source tarballs). Heaviest: lpSolveAPI 479 KB.

Depends (1)
R >= 4.0.0
Imports (4)
statsgraphicsutilslpSolveAPI
LinkingTo (0)
none
Suggests (4)
testthatknitrrmarkdownfrontier
Enhances (0)
none
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People (1)
Erik Enstad ORCID iD
Author, Maintainer since 0.5.0 (2026)
Releases (4)

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Package metadata

First published
2026-07-28
Total releases
4 / 1 yrs
License
GPL (>= 3) OSI
Minimum R
≥ 4.0.0
Bundled data
30 KB / 4 files
Download size
314 KB

Cite

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citation("pgt")

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Cite the R Observatory

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APA

Balamuta, J. J. (2026). R Observatory: Metrics for pgt version 0.7.1 [Data set]. HJJB, LLC. Data release v2026-10-22. https://doi.org/10.5281/zenodo.21843040

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