SdeaR (version 1.0.2)

modelstoch_radial_supereff: Chance Constrained Radial Super-efficiency Models

Description

Solve chance constrained radial super-efficiency DEA models, based on the Cooper et al. (2002) chance constrained radial efficiency models. Analogously to the deterministic case, it removes the evaluated DMU from the set of reference DMUs dmu_ref with respect to which it is evaluated.

Usage

modelstoch_radial_supereff(datadea,
                                  dmu_eval = NULL,
                                  dmu_ref = NULL,
                                  ...)

Value

A list with the results for the evaluated DMUs and other parameters for reproducibility.

Arguments

datadea

The data of class deadata_stoch with the expected values of inputs and 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.

...

Model parameters like orientation or rts, and other parameters to be passed to the solver.

Author

Vicente Bolós (). Department of Business Mathematics

Rafael Benítez (). Department of Business Mathematics

Vicente Coll-Serrano (). Quantitative Methods for Measuring Culture (MC2). Applied Economics.

University of Valencia (Spain)

References

Cooper, W.W.; Deng, H.; Huang, Z.; Li, S.X. (2002). “Chance constrained programming approaches to technical efficiencies and inefficiencies in stochastic data envelopment analysis", Journal of the Operational Research Society, 53:12, 1347-1356.

See Also

modelstoch_radial