slack | R Documentation |
Slacks are calculated after taking the efficiency into consideration.
slack(X, Y, e, XREF = NULL, YREF = NULL, FRONT.IDX = NULL, LP = FALSE, CONTROL=NULL)
X |
Inputs of firms to be evaluated, a K x m matrix of observations of K firms with m inputs (firm x input). |
Y |
Outputs of firms to be evaluated, a K x n matrix of observations of K firms with n outputs (firm x input). |
e |
A Farrell object as returned from |
XREF |
Inputs of the firms determining the technology, defaults
to |
YREF |
Outputs of the firms determining the technology,
defaults to |
FRONT.IDX |
Index for firms determining the technology |
LP |
Set |
CONTROL |
Possible controls to lpSolveAPI, see the
documentation for that package. For examples of use see the
function |
Slacks are calculated in a LP problem where the sum of all slacks are maximised after correction for efficiency. The for calculating slacks for orientation graph is low because of the low precision in the calculated graph efficiency.
The result is returned as the Farrell object used as the argument in the call of the function with the following added components:
slack |
A logical vector where the component for a firm is
|
sum |
A vector with sums of the slacks for each firm. Only
calculated in dea when option |
sx |
A matrix for input slacks for each firm, only calculated
if the option |
sy |
A matrix for output slack, see |
If a numerical problem occurs, status=5, or if no solution can be found,
the best solution is often to scale the input X
and output
Y
yourself or use the option CONTROL
to change scaling in
the program itself, as described in the notes for dea
.
Peter Bogetoft and Lars Otto larsot23@gmail.com
Peter Bogetoft and Lars Otto; Benchmarking with DEA, SFA, and R; Springer 2011. Sect. 5.6 page 127.
WW Cooper, LM Seiford, and K Tone; Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software, 2nd edn. Springer 2007 .
x <- matrix(c(100,200,300,500,100,200,600),ncol=1)
y <- matrix(c(75,100,300,400,25,50,400),ncol=1)
dea.plot.frontier(x,y,txt=1:dim(x)[1])
e <- dea(x,y)
eff(e)
# calculate slacks
sl <- slack(x,y,e)
data.frame(e$eff,sl$slack,sl$sx,sl$sy)
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