direc.dea: Linear Programming for the Directional Distance Function with...

In nonparaeff: Nonparametric Methods for Measuring Efficiency and Productivity

Linear Programming for the Directional Distance Function with Undesirable Outputs

Description

Solve the DDF with undesirable outputs. The directional vecor is (y's, b's).

Usage

  direc.dea(base = NULL, frontier = NULL, ngood = 1, nbad = 1)

Arguments

base	A data set for DMUs to be evaluated. A data frame with J1*(M+P+Q) dimention, where J1 is the number of DMUs, M for the number of inputs, P for the number of good outputs, and Q for the undesirable outputs.
frontier	A data set for DMUs to be used in constructing a production possibility set (PPS). A data frame with J2*(M+P+Q) dimention, where J2 is the number of DMUs, M for the number of inputs, P for the number of good outputs, and Q for the undesirable outputs
ngood	The number of good outputs (P).
nbad	The number of bad outputs (Q).

Details

The DDF with undesirable outputs under the CRS assumption is calculated. For model specification, take a look at Chung et al. (1997).

Value

A J1 vector of which is inefficiency score.

Author(s)

Dong-hyun Oh, [e-mail]

References

Chung, Y. Fare, R. and Grosskopf, S. (1997). Productivity and undesirable outputs: A directional distance function approach. Journal of Environmental Management 51(3):229-240.

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

ddf

Examples

## Simple Example of one input, one good output, and one bad output.
my.dat <- data.frame(yg = c(2, 5, 7, 8, 3, 4, 6),
                     yb = c(1, 2, 4, 7, 4, 5, 6),
                     x = c(1, 1, 1, 1, 1, 1, 1))
direc.dea(my.dat, ngood = 1, nbad = 1)

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