deaR (version 1.2.1)

model_addsupereff: 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

The data, including n DMUs, m inputs and s outputs.

dmu_eval

A numeric vector containing which DMUs have to be evaluated. If NULL (default), all DMUs are considered.

dmu_ref

A numeric vector containing which DMUs are the evaluation reference set. If NULL (default), all DMUs are considered.

orientation

This parameter is either NULL (default) or a string, equal to "io" (input-oriented) or "oo" (output-oriented). It is used to modify the weight slacks. If input-oriented, weight_slack_o are taken 0. If output-oriented, weight_slack_i are taken 0.

weight_slack_i

A value, vector of length m, or matrix m x ne (where ne is the lenght of dmu_eval) with the weights of the input superslacks (t_input). If 0, output-oriented. If weight_slack_i is the matrix of the inverses of inputs (of DMUS in dmu_eval), the model is unit invariant.

weight_slack_o

A value, vector of length s, or matrix s x ne (where ne is the lenght of dmu_eval) with the weights of the output superslacks (t_output). If 0, input-oriented. If weight_slack_o is the matrix of the inverses of outputs (of DMUS in dmu_eval), the model is unit invariant.

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 TRUE, it computes targets, projections and slacks.

returnlp

Logical. If it is TRUE, it returns the linear problems (objective function and constraints).

...

Ignored, for compatibility issues.

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. https://doi.org/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

# NOT RUN {
# Replication of results in Du, Liang and Zhu (2010, Table 6, p.696)
data("Power_plants")
Power_plants <- read_data(Power_plants, 
                          ni = 4, 
                          no = 2)
result <- model_addsupereff(Power_plants, 
                            rts = "crs")  
efficiencies(result)

# }