efficiencies.dea_fuzzy: Efficiencies

In deaR: Conventional and Fuzzy Data Envelopment Analysis

Efficiencies

Description

Extract the scores (optimal objective values) of the evaluated DMUs from a fuzzy DEA solution. Note that these scores may not always be interpreted as efficiencies.

Usage

## S3 method for class 'dea_fuzzy'
efficiencies(x, ...)

Arguments

x	Object of class dea_fuzzy obtained with some of the fuzzy DEA modelfuzzy_* functions.
...	Other options (for compatibility).

Author(s)

Vicente Coll-Serrano ([e-mail]). Quantitative Methods for Measuring Culture (MC2). Applied Economics.

Vicente Bolós ([e-mail]). Department of Business Mathematics

Rafael Benítez ([e-mail]). Department of Business Mathematics

University of Valencia (Spain)

References

Boscá, J.E.; Liern, V.; Sala, R.; Martínez, A. (2011). "Ranking Decision Making Units by Means of Soft Computing DEA Models". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 19(1), p.115-134.

Examples

# Replication of results in Boscá, Liern, Sala and Martínez (2011, p.125)
data("Leon2003")
data_example <- make_deadata_fuzzy(datadea = Leon2003,
                                   inputs.mL = 2, 
                                   inputs.dL = 3, 
                                   outputs.mL = 4, 
                                   outputs.dL = 5)
result <- modelfuzzy_kaoliu(data_example,
                            kaoliu_modelname = "basic", 
                            alpha = seq(0, 1, by = 0.1), 
                            orientation = "io", 
                            rts = "vrs")
efficiencies(result) 

deaR documentation built on May 2, 2023, 5:13 p.m.