infoPlot: Plot absolute and relative information

Description

Plot absolute and relative information of influence curves.

Usage

infoPlot(object,  ...)
## S3 method for class 'IC':
infoPlot(object, data = NULL, ...,
             withSweave = getdistrOption("withSweave"),
             col = par("col"), lwd = par("lwd"), lty, 
             colI = grey(0.5), lwdI = 0.7*par("lwd"), ltyI = "dotted",
             main = FALSE, inner = TRUE, sub = FALSE, 
             col.inner = par("col.main"), cex.inner = 0.8, 
             bmar = par("mar")[1], tmar = par("mar")[3],
             legend.location = "bottomright",
             mfColRow = TRUE, to.draw.arg = NULL,
             cex.pts = 1, col.pts = par("col"),
             pch.pts = 1, jitter.fac = 1, with.lab = FALSE,
             lab.pts = NULL, lab.font = NULL,
             which.lbs = NULL, which.Order  = NULL, return.Order = FALSE)

Arguments

object

object of class "InfluenceCurve"

data

optional data argument --- for plotting observations into the plot;

withSweave

logical: if TRUE (for working with Sweave) no extra device is opened

main

logical: is a main title to be used? or just as argument main in plot.default.

inner

logical: do panels have their own titles? or character vector of / cast to length 'number of compared dimensions'; if argument to.draw.arg is used, this refers to a vector of length 1

sub

logical: is a sub-title to be used? or 
just as argument sub in plot.default.

tmar

top margin -- useful for non-standard main title sizes

bmar

bottom margin -- useful for non-standard sub title sizes

col

color of IC in argument object.

lwd

linewidth of IC in argument object.

lty

line-type of IC in argument object.

colI

color of the classically optimal IC

lwdI

linewidth of the classically optimal IC

ltyI

line-type of the classically optimal IC

cex.inner

magnification to be used for inner titles relative
          to the current setting of cex; as in 
          par

col.inner

character or integer code; color for the inner title

legend.location

a valid argument x for legend ---
                         the place where to put the legend on the last issued
                         plot --- or a list of length (number of plotted panels)

mfColRow

shall default partition in panels be used --- defaults to TRUE

to.draw.arg

Either NULL (default; 
                          everything is plotted) or a vector making a selection
                          among the relative information plots; the absolute
                          information being plotted in any

cex.pts

size of the points of the data argument plotted

col.pts

color of the points of the data argument plotted

pch.pts

symbol of the points of the data argument plotted

with.lab

logical; shall labels be plotted to the observations?

lab.pts

character or NULL; labels to be plotted to the observations; if NULL
                 observation indices;

lab.font

font to be used for labels

jitter.fac

jittering factor used in case of a DiscreteDistribution
                    for plotting points of the data argument in a jittered fashion.

which.lbs

either an integer vector with the indices of the observations
          to be plotted into graph or NULL --- then no observation is excluded

which.Order

we order the observations (descending) according to the norm given by
           normtype(object); then which.Order
           either is an integer vector with the indices of the ordered
           observations (remai

return.Order

logical; if TRUE, a list of length two with order vectors
    is returned --- one for ordering w.r.t. the given IC, one for ordering w.r.t.
    the classically optimal IC; more specifically, the order of the (remaining) observations
    gi

...

further parameters for plot

`concept`

absolute information
relative information

`Details`

Absolute information is defined as the square of the length
  of an IC. The relative information is defined as the 
  absolute information of one component with respect to the 
  absolute information of the whole IC; confer Section 8.1 
  of Kohl (2005). 
Any parameters of plot.default may be passed on to this particular
plot method. 

For main-, inner, and subtitles given as arguments main, 
inner, and sub, top and bottom margins are enlarged to 5 resp. 
6 by default but may also be specified by tmar / bmar arguments. 
If main / inner / sub are 
logical then if the respective argument is FALSE nothing is done/plotted, 
but if it is TRUE, we use a default main title taking up the calling 
arguments in case of main, default inner titles taking up the
class and (named) parameter slots of arguments in case of inner,
and a "generated on "-tag in case of sub.
Of course, if main / inner / sub are character, this
is used for the title; in case of inner it is then checked whether it
has correct length. In all title arguments, the following patterns are substituted:
[object Object],[object Object],[object Object]

If argument ... contains argument ylim, this may either be
as in plot.default (i.e. a vector of length 2) or a vector of 
length 2*(number of plotted dimensions + e), where e is 1 or 0 depending
on whether absolute information is plotted or not; 
in the case of longer length, 
if e is 1, the first two elements are the values for ylim 
in panel "Abs", while the last 2*(number of plotted dimensions)
are the values for ylim for the plotted dimensions of the IC, 
one pair for each dimension.

`References`

Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. 
  Bayreuth: Dissertation.

`See Also`

L2ParamFamily-class, IC-class

`Examples`

Run this codeN <- NormLocationScaleFamily(mean=0, sd=1) 
IC1 <- optIC(model = N, risk = asCov())
infoPlot(IC1)
## selection of subpanels for plotting
par(mfrow=c(1,2))
infoPlot(IC1, mfColRow = FALSE, to.draw.arg=c("Abs","sd"))
infoPlot(IC1, mfColRow = FALSE, to.draw.arg=c("Abs","mean"), 
              panel.first= grid(), ylim = c(0,4), xlim = c(-6,6))
infoPlot(IC1, mfColRow = FALSE, to.draw.arg=c("Abs","mean"), 
              panel.first= grid(), ylim = c(0,4,-3,3), xlim = c(-6,6))
par(mfrow=c(1,3))
infoPlot(IC1, mfColRow = FALSE, panel.first= grid(),
         ylim = c(0,4,0,.3,0,.8), xlim=c(-6,6))
par(mfrow=c(1,1))
data <- r(N)(20)
par(mfrow=c(1,3))
infoPlot(IC1, data=data, mfColRow = FALSE, panel.first= grid(),
         with.lab = TRUE, cex.pts=2,
         which.lbs = c(1:4,15:20), which.Order = 1:6,
         return.Order = TRUE)
infoPlot(IC1, data=data[1:10], mfColRow = FALSE, panel.first= grid(),
         with.lab = TRUE, cex.pts=0.7)
par(mfrow=c(1,1))
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