map.soa.sf: SOA mapping using SF
In DJL: Distance Measure Based Judgment and Learning

map.soa.sf

R Documentation

SOA mapping using SF

Description

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

Usage

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).

Examples

# 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")

DJL documentation built on March 31, 2023, 9:05 p.m.