View source: R/model_supereff.R
| model_supereff | R Documentation |
Solve Andersen and Petersen radial Super-efficiency DEA model.
model_supereff(datadea,
dmu_eval = NULL,
dmu_ref = NULL,
supereff_modelname = c("basic"),
...)
datadea |
An object of class |
dmu_eval |
A numeric vector containing which DMUs have to be evaluated.
If |
dmu_ref |
A numeric vector containing which DMUs are the evaluation reference set.
If |
supereff_modelname |
A string containing the name of the radial model to apply super-efficiency. |
... |
|
A list of class dea with the results for the evaluated DMUs (DMU component,
we note that we call "targets" to the "efficient projections"
in the strongly efficient frontier),
along with any other necessary information to replicate the results, such as
the name of the model and parameters orientation, rts,
dmu_eval and dmu_ref.
(1) Radial super-efficiency model under variable (vrs, nirs, ndrs, grs) returns to scale can be infeasible for certain DMUs. See example 2.
(2) DMUs with infeasible solution are not shown in the results.
Vicente Coll-Serrano (vicente.coll@uv.es). Quantitative Methods for Measuring Culture (MC2). Applied Economics.
Vicente Bolós (vicente.bolos@uv.es). Department of Business Mathematics
Rafael Benítez (rafael.suarez@uv.es). Department of Business Mathematics
University of Valencia (Spain)
Andersen, P.; Petersen, N.C. (1993). "A procedure for ranking efficient units in data envelopment analysis", Management Science, 39, 1261-1264.
Tone, K. (2002). "A slacks-based measure of super-efficiency in data envelopment analysis", European Journal of Operational Research, 143, 32-41.
model_basic, model_sbmsupereff,
model_addsupereff
# Example 1.
# Replication of results in Tone (2002, p.38)
data("Power_plants")
data_example <- make_deadata(Power_plants,
ni = 4,
no = 2)
result <- model_supereff(data_example,
orientation = "io",
rts = "crs")
eff <- efficiencies(result)
# Example 2.
# Results of Super-efficiency with vrs returns to scale show infeasibility solutions
# for DMUs D4 and D6 (these DMUs are not shown in deaR results).
data("Power_plants")
data_example2 <- make_deadata(Power_plants,
ni = 4,
no = 2)
result2 <- model_supereff(data_example2,
orientation = "io",
rts = "vrs")
eff2 <- efficiencies(result2)
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