direc.dea {nonparaeff} | R Documentation |
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, oh.donghyun77@gmail.com
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
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)