Description Usage Arguments Details Value References See Also Examples
Estimates a Data Envelopment Analysis frontier and calculates efficiency measures
1 2 |
x |
Inputs or resources used by each decision making unit. | |||||||||
y |
Outputs or products of each decision making unit. Must have same number of rows
as | |||||||||
rts |
Returns to scale for the application, production technology, or industry studied
| |||||||||
orientation |
Orientation of the DEA model - primary emphasis on input-reduction | |||||||||
slack |
Optional: | |||||||||
dual |
Optional: | |||||||||
round |
Optional: | |||||||||
second |
Optional: Enables an alternate secondary objective function based on lambda and
the z argument. The default is | |||||||||
z |
Optional:a matrix with one column and the same number of rows (decision making units) as x
and y, it is only used when | |||||||||
debug |
Optional: Only for debugging. If |
This DEA function draws inspiration from previous R packages for doing DEA including Benchmarking and FEAR. As such it was designed to use similar parameters and return similar results to allow users to switch between packages. The DEA function was developed to support a function for doing Technology Forecasting using Data Envelopment Analysis or TFDEA. In particular, TFDEA requires an option to resolve multiple optima that is similar to but different from the standard slack maximization approach in Data Envelopment Analysis. This feature is exposed through DEA function's second and z parameters.
$status |
If the solver returned a non-zero status for each decision making unit |
$eff |
Efficiency score for each decision making unit |
$lambda |
Lambda values for each decision making unit |
$vx |
Input weights used by each decision making unit, only returned when dual=TRUE |
$uy |
Output weights used by each decision making unit, only returned when dual=TRUE |
$w |
W value for each decision making unit, only returned when dual=TRUE |
$sx |
Radial input slacks, only returned when slack=TRUE |
$sy |
Radial output slacks, only returned when slack=TRUE |
Bogetoft and Otto; Benchmarking with DEA, SFA, and R; Springer 2011
Paul W. Wilson (2008), FEAR 1.0: A Software Package for Frontier Efficiency Analysis with R, Socio-Economic Planning Sciences 42, 247-254
SDEA
Super-efficiency - an extension to regular DEA that allows for differentiating
between efficient DMUs.
TFDEA
Technology Forecasting using Data Envelopment Analysis - a method of technology
forecasting using past data to predict future capabilities
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | x <- matrix(c(8,2,4,7,2,8,4,3),ncol=2,dimnames=list(LETTERS[1:4]))
colnames(x) = c("X1", "X2")
y <- matrix(c(1,1,1,1),ncol=1,dimnames=list(LETTERS[1:4],"Y"))
# Simple radial DEA efficiency
DEA(x, y, rts="crs", orientation="input")
# Simple radial DEA efficiency with slack maximization
DEA(x, y, rts="crs", orientation="input", slack=TRUE)
# Example of secondary objective function
x <- matrix(c(8,2,4,7,10,12,2,8,4,3,2,2),ncol=2,dimnames=list(LETTERS[1:6]))
colnames(x) = c("X1", "X2")
y <- matrix(c(1,1,1,1,1,1),ncol=1,dimnames=list(LETTERS[1:6],"Y"))
z <- matrix(c(1:6),ncol=1,dimnames=list(LETTERS[1:6],"Z"))
DEA (x,y,rts="crs", orientation="input", round=TRUE, slack=FALSE,
second="min", z=z)
DEA (x,y,rts="crs", orientation="input", round=TRUE, slack=FALSE,
second="max", z=z)
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