We generalize function qqplot from package stats to
be applicable to distribution and probability model objects. In this context,
qqplot produces a QQ plot of data (argument x) against
a (model) distribution. For arguments y of class RobModel,
points at a high “distance” to the model
are plotted smaller. For arguments y of class kStepEstimate,
points at with low weight in the [p]IC are plotted bigger and their
color gets faded out slowly.
Graphical parameters may be given as arguments to qqplot.
qqplot(x, y, ...)
# S4 method for ANY,RobModel
qqplot(x, y,
n = length(x), withIdLine = TRUE, withConf = TRUE,
withConf.pw = withConf, withConf.sim = withConf,
plot.it = TRUE, xlab = deparse(substitute(x)),
ylab = deparse(substitute(y)), ..., distance = NormType(),
n.adj = TRUE)
# S4 method for ANY,InfRobModel
qqplot(x, y, n = length(x), withIdLine = TRUE,
withConf = TRUE, withConf.pw = withConf, withConf.sim = withConf,
plot.it = TRUE, xlab = deparse(substitute(x)), ylab =
deparse(substitute(y)), ..., cex.pts.fun = NULL, n.adj = TRUE)
# S4 method for ANY,kStepEstimate
qqplot(x, y,
n = length(x), withIdLine = TRUE, withConf = TRUE,
withConf.pw = withConf, withConf.sim = withConf,
plot.it = TRUE, xlab = deparse(substitute(x)),
ylab = deparse(substitute(y)), ...,
exp.cex2.lbs = -.15,
exp.cex2.pts = -.35,
exp.fadcol.lbs = 1.85,
exp.fadcol.pts = 1.85,
bg = "white")As for function qqplot from package stats: a
list with components
The x coordinates of the points that were/would be plotted
The corresponding quantiles of the second distribution,
including NAs.
data to be checked for compatibility with distribution/model y.
object of class "RobModel", of class "InfRobModel" or of
class "kStepEstimate".
numeric; number of quantiles at which to do the comparison.
logical; shall line y = x be plotted in?
logical; shall confidence lines be plotted?
logical; shall pointwise confidence lines be plotted?
logical; shall simultaneous confidence lines be plotted?
logical; shall be plotted at all (inherited from qqplot)?
x-label
y-label
further parameters for method qqplot with signature
ANY,ProbFamily (see qqplot) or with function plot
rescaling function for the size of the points to be plotted;
either NULL (default), then log(1+abs(x)) is used,
or a function which is then used.
logical; shall sample size be adjusted for possible outliers according to radius of the corresponding neighborhood?
a function mapping observations x to the positive reals;
used to determine the size of the plotted points (the larger distance(x),
the smaller the points are plotted.
for objects kStepEstimate based on a [p]IC of class HampIC:
exponent for the weights of this [p]IC used to magnify the labels.
for objects kStepEstimate based on a [p]IC of class HampIC:
exponent for the weights of this [p]IC used to magnify the symbols.
for objects kStepEstimate based on a [p]IC of class HampIC:
exponent for the weights of this [p]IC used to find out-fading colors.
for objects kStepEstimate based on a [p]IC of class HampIC:
exponent for the weights of this [p]IC used to find out-fading colors.
background color to fade against
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de
signature(x = "ANY", y = "RobModel"):
produces a QQ plot of a dataset x against the theoretical
quantiles of distribution of robust model y.
signature(x = "ANY", y = "InfRobModel"):
produces a QQ plot of a dataset x against the theoretical
quantiles of distribution of infinitesimally robust model y.
signature(x = "ANY", y = "kStepEstimate"):
produces a QQ plot of a dataset x against the theoretical
quantiles of the model distribution of model at which
the corresponding kStepEstimate y had been calibrated at.
By default, if the [p]IC of the kStepEstimate is of class
HampIC, i.e.; has a corresponding weight function,
points (and, if with.lab==TRUE, labels) are
scaled and faded according to this weight function. Corresponding
arguments exp.cex2.pts and exp.fadcol.pts control this
scaling and fading, respectively
(and analogously exp.cex2.lbs and exp.fadcol.lbs for the labels).
The choice of these arguments has to be done on a case-by-case basis.
Positive exponents induce fading, magnification with increasing weight,
for negative exponents the same is true for decreasing weight; higher
(absolute) values increase the speed of fading / magnification.
Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.
qqplot from package stats -- the standard QQ plot
function, qqplot from package distr for
comparisons of distributions, and
qqplot from package distrMod (which
is called intermediately by this method), as well as
qqbounds, used by qqplot to produce confidence
intervals.
## \donttest to reduce check time
# \donttest{
qqplot(rnorm(40, mean = 15, sd = sqrt(30)), Chisq(df=15))
RobM <- InfRobModel(center = NormLocationFamily(mean=13,sd=sqrt(28)),
neighbor = ContNeighborhood(radius = 0.4))
x <- rnorm(20, mean = 15, sd = sqrt(30))
qqplot(x, RobM)
qqplot(x, RobM, alpha.CI=0.9, add.points.CI=FALSE)
# }
## further examples for ANY,kStepEstimator-method
## in example to roptest() in package ROptEst
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