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R: Distance measure using DEA

dm.dea

R Documentation

Distance measure using DEA

Description

Implements Charnes & Cooper's data envelopment analysis (radial & oriented measure).

Usage

dm.dea(xdata, ydata, rts, orientation,
       se=0, sg="ssm", date=NULL, ncv=NULL, env=NULL)

Arguments

`xdata`	Input(s) vector (n by m)
`ydata`	Output(s) vector (n by s)
`rts`	Returns to scale assumption `"crs"` Constant RTS `"vrs"` Variable RTS `"irs"` Increasing RTS `"drs"` Decreasing RTS
`orientation`	Orientation of the measurement `"i"` Input-orientation `"o"` Output-orientation
`se`	Implements Anderson & Peterson's super-efficiency model if `1`
`sg`	Employs second-stage optimization `"ssm"` Slack-sum maximization (default) `"max"` Date-sum maximization (only if `date` is defined) `"min"` Date-sum minimization (only if `date` is defined)
`date`	Production date (n by 1)
`ncv`	Non-controllable variable index(binary) for internal NDF (1 by (m+s))
`env`	Environment index for external NDF (n by 1)

Value

`$eff`	Efficiency score
`$lambda`	Intensity vector
`$xslack`	Input slack
`$yslack`	Output slack
`$vx`	Input (dual) weight
`$uy`	Output (dual) weight
`$w`	Free (dual) variable

Author(s)

Dong-Joon Lim, PhD

References

Charnes, Abraham, William W. Cooper, and Edwardo Rhodes. "Measuring the efficiency of decision making units." European journal of operational research 2.6 (1978): 429~444.

Banker, Rajiv D., Abraham Charnes, and William Wager Cooper. "Some models for estimating technical and scale inefficiencies in data envelopment analysis." Management science 30.9 (1984): 1078~1092.

Banker, Rajiv D., and Richard C. Morey. "Efficiency analysis for exogenously fixed inputs and outputs." Operations Research 34.4 (1986): 513~521.

Ruggiero, John. "On the measurement of technical efficiency in the public sector." European Journal of Operational Research 90.3 (1996): 553~565.

Fried, Harold O., CA Knox Lovell, and Shelton S. Schmidt, eds. The measurement of productive efficiency and productivity growth. Oxford University Press, 2008.

Examples

# Reproduce Table 3.9 (p.348) in Fried, H.O. et al.(2008)
  # ready
  x<-matrix(c(8,6,3,10,6,8,8,4,8,4.6,1.9,9,3.6,3.6,9,1.9),ncol=2)
  y<-matrix(c(8,5,2,9,4.5,4.5,7,2),ncol=1)
  c<-matrix(c(0,1,0),nrow=1)
  
  # go
  dm.dea(x,y,"crs","i")$eff
  dm.dea(x,y,"vrs","i")$eff
  dm.dea(x,y,"crs","i",ncv=c)$eff
  dm.dea(x,y,"vrs","i",ncv=c)$eff

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(DJL)
Loading required package: car
Loading required package: combinat

Attaching package: 'combinat'

The following object is masked from 'package:utils':

    combn

Loading required package: lpSolveAPI
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/DJL/dm.dea.Rd_%03d_medium.png", width=480, height=480)
> ### Name: dm.dea
> ### Title: Distance measure using DEA
> ### Aliases: dm.dea
> 
> ### ** Examples
> 
> # Reproduce Table 3.9 (p.348) in Fried, H.O. et al.(2008)
>   # ready
>   x<-matrix(c(8,6,3,10,6,8,8,4,8,4.6,1.9,9,3.6,3.6,9,1.9),ncol=2)
>   y<-matrix(c(8,5,2,9,4.5,4.5,7,2),ncol=1)
>   c<-matrix(c(0,1,0),nrow=1)
>   
>   # go
>   dm.dea(x,y,"crs","i")$eff
          [,1]
[1,] 1.0000000
[2,] 0.9756098
[3,] 0.8648649
[4,] 0.9600000
[5,] 1.0000000
[6,] 1.0000000
[7,] 0.8750000
[8,] 0.8421053
>   dm.dea(x,y,"vrs","i")$eff
          [,1]
[1,] 1.0000000
[2,] 0.9892086
[3,] 1.0000000
[4,] 1.0000000
[5,] 1.0000000
[6,] 1.0000000
[7,] 0.8958333
[8,] 1.0000000
>   dm.dea(x,y,"crs","i",ncv=c)$eff
          [,1]
[1,] 1.0000000
[2,] 0.9330986
[3,] 1.0000000
[4,] 0.9000000
[5,] 0.8973214
[6,] 0.6729911
[7,] 0.8750000
[8,] 0.7500000
>   dm.dea(x,y,"vrs","i",ncv=c)$eff
          [,1]
[1,] 1.0000000
[2,] 0.9801980
[3,] 1.0000000
[4,] 1.0000000
[5,] 1.0000000
[6,] 0.7500000
[7,] 0.8958333
[8,] 0.7500000
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>