RobAStBase: qqplot – R documentation

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qqplot

Methods for Function qqplot in Package ‘RobAStBase’

Description

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.

Usage

qqplot(x, y, ...)
## S4 method for signature '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 signature '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 signature '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")

Arguments

`x`	data to be checked for compatibility with distribution/model `y`.
`y`	object of class `"RobModel"`, of class `"InfRobModel"` or of class `"kStepEstimate"`.
`n`	numeric; number of quantiles at which to do the comparison.
`withIdLine`	logical; shall line `y = x` be plotted in?
`withConf`	logical; shall confidence lines be plotted?
`withConf.pw`	logical; shall pointwise confidence lines be plotted?
`withConf.sim`	logical; shall simultaneous confidence lines be plotted?
`plot.it`	logical; shall be plotted at all (inherited from `qqplot`)?
`xlab`	x-label
`ylab`	y-label
`...`	further parameters for method `qqplot` with signature `ANY,ProbFamily` (see `qqplot`) or with function `plot`
`cex.pts.fun`	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.
`n.adj`	logical; shall sample size be adjusted for possible outliers according to radius of the corresponding neighborhood?
`distance`	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.
`exp.cex2.lbs`	for objects `kStepEstimate` based on a [p]IC of class `HampIC`: exponent for the weights of this [p]IC used to magnify the labels.
`exp.cex2.pts`	for objects `kStepEstimate` based on a [p]IC of class `HampIC`: exponent for the weights of this [p]IC used to magnify the symbols.
`exp.fadcol.lbs`	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.
`exp.fadcol.pts`	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.
`bg`	background color to fade against

Details

qqplot: signature(x = "ANY", y = "RobModel"): produces a QQ plot of a dataset x against the theoretical quantiles of distribution of robust model y.
qqplot: signature(x = "ANY", y = "InfRobModel"): produces a QQ plot of a dataset x against the theoretical quantiles of distribution of infinitesimally robust model y.
qqplot: 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.

Value

As for function qqplot from package stats: a list with components

`x`	The x coordinates of the points that were/would be plotted
`y`	The corresponding quantiles of the second distribution, including `NA`s.

Author(s)

Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de

References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) The New S Language. Wadsworth & Brooks/Cole.

Examples

## \donttest to reduce check time

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

RobAStBase

Robust Asymptotic Statistics

v1.2.1

LGPL-3

Authors

Matthias Kohl [cre, cph, aut], Peter Ruckdeschel [aut, cph], Mykhailo Pupashenko [ctb] (contributed wrapper functions for diagnostic plots), Gerald Kroisandt [ctb] (contributed testing routines), R Core Team [ctb, cph] (for source file 'format.perc')

Initial release

2019-04-07