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.
## 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).
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)
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.