SOA mapping using SF

Description

Employs dm.sf over time to generate a state-of-the-art map.

Usage

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map.soa.sf(xdata, ydata, date, 
           rts="crs", g=NULL, wd=NULL, sg="ssm", cv="convex", mk="dmu")

Arguments

xdata

Input(s) vector (n by m)

ydata

Output(s) vector (n by s)

date

Production date (n by 1)

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)

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)

cv

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

mk

Marker on the map
"dmu" DMU index (default)
"eff" Efficiency score

Author(s)

Dong-Joon Lim, PhD

References

D.-J. Lim, Internal combustion engine race: naturally aspirated vs turbo/super-charged, working paper (2015).

See Also

map.soa.ddf SOA mapping using DDF
map.soa.dea SOA mapping using DEA
map.soa.hdf SOA mapping using HDF
map.soa.sbm SOA mapping using SBM
map.soa.sf SOA mapping using SF

Examples

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# Reproduce Table 2 in Lim, D-J. (2015)
  # Load engine dataset
    df <- dataset.engine.2015
  
  # Subset for 4 cylinder engines
    fce <- subset(df, df[, 3] == 4)

  # Parameters
    x <- subset(fce, select = 4)
    y <- subset(fce, select = 5 : 7)
    d <- subset(fce, select = 2)
    g <- data.frame(0, y)
    w <- matrix(c(1, 0, 0), ncol = 3)

  # Generate an SOA map
    map.soa.sf(x, y, d, "crs", g, w, mk = "eff")