model_addsupereff {deaR} | R Documentation |
Additive super-efficiency DEA model.
Description
Solve the additive super-efficiency model proposed by Du, Liang and Zhu (2010). It is an extension of the SBM super-efficiency to the additive DEA model.
Usage
model_addsupereff(datadea,
dmu_eval = NULL,
dmu_ref = NULL,
orientation = NULL,
weight_slack_i = NULL,
weight_slack_o = NULL,
rts = c("crs", "vrs", "nirs", "ndrs", "grs"),
L = 1,
U = 1,
compute_target = TRUE,
returnlp = FALSE,
...)
Arguments
datadea |
A |
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 |
orientation |
This parameter is either |
weight_slack_i |
A value, vector of length |
weight_slack_o |
A value, vector of length |
rts |
A string, determining the type of returns to scale, equal to "crs" (constant), "vrs" (variable), "nirs" (non-increasing), "ndrs" (non-decreasing) or "grs" (generalized). |
L |
Lower bound for the generalized returns to scale (grs). |
U |
Upper bound for the generalized returns to scale (grs). |
compute_target |
Logical. If it is |
returnlp |
Logical. If it is |
... |
Ignored, for compatibility issues. |
Author(s)
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)
References
Du, J.; Liang, L.; Zhu, J. (2010). "A Slacks-based Measure of Super-efficiency in Data Envelopment Analysis. A Comment", European Journal of Operational Research, 204, 694-697. doi:10.1016/j.ejor.2009.12.007
Zhu, J. (2014). Quantitative Models for Performance Evaluation and Benchmarking. Data Envelopment Analysis with Spreadsheets. 3rd Edition Springer, New York. doi:10.1007/978-3-319-06647-9
See Also
model_additive
, model_supereff
,
model_sbmsupereff
Examples
# Replication of results in Du, Liang and Zhu (2010, Table 6, p.696)
data("Power_plants")
Power_plants <- make_deadata(Power_plants,
ni = 4,
no = 2)
result <- model_addsupereff(Power_plants,
rts = "crs")
efficiencies(result)