Distance measure using DDF

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Description

Implements Chambers' directional distance function (non-radial & non-oriented measure).

Usage

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dm.ddf(xdata, ydata, rts="crs", g=NULL, 
       wd=NULL, se=FALSE, sg="ssm", date=NULL, cv="convex", o=NULL)

Arguments

xdata

Input(s) vector (n by m)

ydata

Output(s) vector (n by s)

rts

Returns to scale assumption
"crs" Constant RTS (default)
"vrs" Variable RTS
"irs" Increasing RTS
"drs" Decreasing RTS

g

Directional vector indicating a measurement direction (n by (m+s))
By default (NULL), xdata & ydata will be used

wd

Weak disposability vector indicating (an) undesirable output(s) (1 by s)

se

Implements super-efficiency model alike Anderson & Peterson's model if TRUE

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)

cv

Convexity assumption
"convex" Convexity holds (default)
"fdh" Free disposal hull (this will override rts)

o

DMU index to calc. NULL(default) will calc for all

Value

$eff

Efficiency score

$lambda

Intensity vector

$mu

Secondary intensity vector for weak disposability under VRS

$beta

Input reduction factor

$gamma

Output augmentation factor

$xslack

Input slack

$yslack

Output slack

Author(s)

Dong-Joon Lim, PhD

References

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.

Fare, Rolf, and Shawna Grosskopf. "Directional distance functions and slacks-based measures of efficiency." European journal of operational research 200.1 (2010): 320~322.

See Also

dm.ddf Distance measure using DDF
dm.dea Distance measure using DEA
dm.hdf Distance measure using HDF
dm.sbm Distance measure using SBM
dm.sf Distance measure using SF

Examples

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# Additive form directional distance 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.ddf(x, y, "crs", g, w)

# Multiplicative form directional distance function
  # ready
  g <- cbind(x, y)
  # go
  dm.ddf(x, y, "crs", g, w)