dual.dea: Linear Programming for the Dual Data Envelopment Analysis

In nonparaeff: Nonparametric Methods for Measuring Efficiency and Productivity

Linear Programming for the Dual Data Envelopment Analysis

Description

Solve the Dual DEA

Usage

dual.dea(base = NULL, frontier = NULL, noutput = 1, orientation=1, rts = 1)

Arguments

base	A data set for DMUs to be evaluated. A data frame with J1*(M+N) dimention, where J1 is the number of DMUs, M for the number of inputs, and N for the number of outputs.
frontier	A data set for DMUs to be used in constructing a production possibility set (PPS). A data frame with J2*(M+N) dimention, where J2 is the number of DMUs, M for the number of inputs, and N for the number of outputs.
noutput	The number of outputs (N).
orientation	Orientation of measurement. 1 for the input-oriented measure, and 2 for the output-oriented measure.
rts	Returns to scale. 1 for the CRS assumption, and 2 for the VRS assumption.

Details

The input-oriented dual DEA under the CRS assumption is calculated. For model specification, take a look at Cooper et al. (2007).

Value

A data frame with J1*(1+M+N) dimension, of which has efficiency scores, optimal virtual prices for inputs and outputs.

Author(s)

Dong-hyun Oh, [e-mail]

References

Cooper, W., Seiford, L. and Tone, K. (2007). Data envelopment analysis: a comprehensive text with models, applications, references and DEA-solver software (2nd ed.). Springer Verlag, New York.

Lee, J. and Oh, D. (forthcoming). Efficiency Analysis: Data Envelopment Analysis. Press (in Korean).

See Also

dea

Examples

## An output-oriented primal problem with 1 input and 2 outputs
tab5.1.dat <- data.frame(y1 = c(4, 8, 8, 4, 3, 1),
                               y2 = c(9, 6, 4, 3, 5, 6),
                               x = c(1, 1, 1, 1, 1, 1))
(re <- dea(tab5.1.dat, noutput = 2, orientation = 2, rts = 1))

## An output-oriented dual problem with 1 input and 2 outputs
re <- dual.dea(tab5.1.dat, noutput = 2, orientation = 2, rts = 1)

nonparaeff documentation built on June 21, 2022, 9:05 a.m.