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Last data update: 2014.03.03

R: Distance measure using SF

dm.sf

R Documentation

Distance measure using SF

Description

Implements Luenberger's shortage function (radial & non-oriented measure).

Usage

dm.sf(xdata, ydata, rts, g, w=NULL, se=0, sg="ssm", date=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
`g`	Directional vector indicating a measurement direction (n by (m+s))
`w`	Weak disposability vector indicating (an) undesirable output(s) (1 by s)
`se`	Implements super-efficiency model alike Anderson & Peterson's 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)

Value

`$eff`	Efficiency score
`$lambda`	Intensity vector
`$mu`	Secondary intensity vector for weak disposability under VRS
`$xslack`	Input slack
`$yslack`	Output slack

Author(s)

Dong-Joon Lim, PhD

References

Luenberger, David G. "Benefit functions and duality." Journal of mathematical economics 21.5 (1992): 461~481.

Chambers, Robert G., Yangho Chung, and Rolf Fare. "Profit, directional distance functions, and Nerlovian efficiency." Journal of optimization theory and applications 98.2 (1998): 351~364.

Examples

# Additive form shortage function
  # ready
  x<-matrix(c(5,1,4),ncol=1)
  y<-matrix(c(8,3,5,6,4,1),ncol=2)
  g<-matrix(c(1),nrow=3,ncol=3) 
  w<-matrix(c(1,0),ncol=2)
  # go
  dm.sf(x,y,"crs",g,w)

# Multiplicative form shortage function
  # ready
  g<-data.frame(x,y)
  # go
  dm.sf(x,y,"crs",g,w)

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.
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Type 'license()' or 'licence()' for distribution details.

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Type 'demo()' for some demos, 'help()' for on-line help, or
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> 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.sf.Rd_%03d_medium.png", width=480, height=480)
> ### Name: dm.sf
> ### Title: Distance measure using SF
> ### Aliases: dm.sf
> 
> ### ** Examples
> 
> # Additive form shortage function
>   # ready
>   x<-matrix(c(5,1,4),ncol=1)
>   y<-matrix(c(8,3,5,6,4,1),ncol=2)
>   g<-matrix(c(1),nrow=3,ncol=3) 
>   w<-matrix(c(1,0),ncol=2)
>   # go
>   dm.sf(x,y,"crs",g,w)
$eff
         [,1]
[1,] 2.000000
[2,] 0.000000
[3,] 2.428571

$lambda
     [,1]      [,2] [,3]
[1,]    0 2.0000000    0
[2,]    0 1.0000000    0
[3,]    0 0.8571429    0

$mu
     [,1] [,2] [,3]
[1,]    0    0    0
[2,]    0    0    0
[3,]    0    0    0

$xslack
          [,1]
[1,] 1.0000000
[2,] 0.0000000
[3,] 0.7142857

$yslack
     [,1] [,2]
[1,]    0    0
[2,]    0    0
[3,]    0    0

> 
> # Multiplicative form shortage function
>   # ready
>   g<-data.frame(x,y)
>   # go
>   dm.sf(x,y,"crs",g,w)
$eff
          [,1]
[1,] 0.2800000
[2,] 0.0000000
[3,] 0.7391304

$lambda
     [,1]      [,2] [,3]
[1,]    0 1.9200000    0
[2,]    0 1.0000000    0
[3,]    0 0.4347826    0

$mu
     [,1] [,2] [,3]
[1,]    0    0    0
[2,]    0    0    0
[3,]    0    0    0

$xslack
          [,1]
[1,] 1.6800000
[2,] 0.0000000
[3,] 0.6086957

$yslack
     [,1] [,2]
[1,]    0    0
[2,]    0    0
[3,]    0    0

> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>