eff.dens {Benchmarking} | R Documentation |
Estimate and plot density of efficiencies
Description
A method to estimate and plot kernel estimate of (Farrell) efficiencies taken into consideration that efficiencies are bounded either above (input direction) or below (output direction).
Usage
eff.dens(eff, bw = "nrd0")
eff.dens.plot(obj, bw = "nrd0", ..., xlim, ylim, xlab, ylab)
Arguments
eff |
Either a list of (Farrell) efficiencies or a Farrell
object returned from the method |
bw |
Bandwith, look at the documentation of |
obj |
Either an array of efficiencies or a list returned from
|
... |
Further arguments to the |
xlim |
Range on the x-axis; usually not needed, just use the defaults. |
ylim |
Range on the x-axis; usually not needed, just use the defaults. |
xlab |
Label for the x-axis. |
ylab |
Label for the y-axis. |
Details
The calculation is based on a reflection method (Silverman
1986, 30) using the default window kernel and default bandwidth (window
width) in the method density
.
The method eff.dens.plot
plot the density directly, and
eff.dens
just estimate the numerical density, and the result
can then either be plotted by plot
, corresponds to
eff.dens.plot
, or by lines as an overlay on an existing plot.
Value
The return from eff.dens
is a list list(x,y)
with efficiencies and the corresponding density values.
Note
The input efficiency is also bounded below by 0, but for normal firms an efficiency at 0 will not happen, i.e. the boundary is not effective, and therefore this boundary is not taken into consideration.
Author(s)
Peter Bogetoft and Lars Otto larsot23@gmail.com
References
B.W. Silverman (1986), Density Estimation for Statistics and Data Analysis, Chapman and Hall, London.
Examples
e <- 1 - rnorm(100)
e[e>1] <- 1
e <- e[e>0]
eff.dens.plot(e)
hist(e, breaks=15, freq=FALSE, xlab="Efficiency", main="")
den <- eff.dens(e)
lines(den,lw=2)