Benchmarking (version 0.10)

add.dea: Additive DEA model

Description

Calculates efficiency as sum of input and output slacks

Usage

add.dea(X, Y, RTS = "vrs", TRANSPOSE = FALSE, ...)

Arguments

X

input where efficiency is to be calculated, a K x m matrix of observations of K firms with m inputs (firm x input). In case TRABSPOSE=TRUE the input matrix is transposed as input x firm.

Y

output where efficiency is to be calculated, a K x n matrix of observations of K firms with n outputs (firm x input). In case TRABSPOSE=TRUE the output matrix is transposed as output x firm.

RTS

A text string or a number to state the returns to scale assumption rcl{ 0 "fdh" Free disposability hull, no convexity assumption 1 "vrs" Variable returns to scale, convex and free disposability 2 "drs" Decreasing returns

TRANSPOSE

Input and output matrices are treated as goods times units as defaults. If TRANSPOSE=FALSE then marices are units times goods as in standard in R for statistical models

...

Optional parameters for the method slack.

Value

• sum
  Sum of all slacks for each unit
• slack
  A non-NULL vector of logical variables, TRUE if there is slack for the corresponding firm: also output from method slack.
• sx
  A matrix for input slacks for each firm, only calculated if the option SLACK is TRUE or returned from the method slack
• sy
  A matrix for output slack, see sx

source

corresponds to eqs. 4.34-4.38 in Cooper et al., 2007

Details

~~ If necessary, more details than the __description__ above ~~

References

B&O

Examples

x <- matrix(c(2,3,2,4,6,5,6,8),ncol=1)
y <- matrix(c(1,3,2,3,5,2,3,5),ncol=1)
dea.plot.frontier(x,y,txt=1:dim(x)[1])

sb <- add.dea(x,y,RTS="vrs")
data.frame("sx"=sb$sx,"sy"=sb$sy,"sum"=sb$sum,"slack"=sb$slack)