slack {Benchmarking}  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 maximied 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 
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 DEASolver 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)