qqplot: Methods for Function qqplot in Package 'distr'

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

We generalize function qqplot from package stats to be applicable to distribution objects. In this context, qqplot produces a QQ plot of two distributions, i.e.; argument x is the distribution to be checked for compatibility, and y is the model (H0-)distribution. Graphical parameters may be given as arguments to qqplot. The stats function is just the method for signature x=ANY,y=ANY. In all title and axis label arguments, if withSubst is TRUE, the following patterns are substituted:

"%C"

class of argument x

"%A"

deparsed argument x

"%D"

time/date-string when the plot was generated

Usage

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qqplot(x, y, ...)
## S4 method for signature 'UnivariateDistribution,UnivariateDistribution'
qqplot(x, y,
    n = 30, withIdLine = TRUE, withConf = TRUE,
    withConf.pw  = withConf,  withConf.sim = withConf,
    plot.it = TRUE, xlab = deparse(substitute(x)),
    ylab = deparse(substitute(y)), ...,
    width = 10, height = 5.5, withSweave = getdistrOption("withSweave"),
    mfColRow = TRUE, n.CI = n, col.IdL = "red", lty.IdL = 2, lwd.IdL = 2,
    alpha.CI = .95, exact.pCI = (n<100), exact.sCI = (n<100), nosym.pCI = FALSE,
    col.pCI = "orange", lty.pCI = 3, lwd.pCI = 2, pch.pCI = par("pch"),
    cex.pCI = par("cex"),
    col.sCI = "tomato2", lty.sCI = 4, lwd.sCI = 2, pch.sCI = par("pch"),
    cex.sCI = par("cex"),
    cex.pch = par("cex"), col.pch = par("col"),
    jit.fac = 0, check.NotInSupport = TRUE,
    col.NotInSupport = "red", with.legend = TRUE, legend.bg = "white",
    legend.pos = "topleft", legend.cex = 0.8, legend.pref = "", 
    legend.postf = "", legend.alpha = alpha.CI, debug = FALSE, withSubst = TRUE)
## S4 method for signature 'ANY,ANY'
qqplot(x, y,
    plot.it = TRUE, xlab = deparse(substitute(x)),
    ylab = deparse(substitute(y)), ...)

Arguments

x

object of class "ANY" (stats-method) or of code "UnivariateDistribution"; to be compared to y.

y

object of class "ANY" (stats-method) or of class "UnivariateDistribution".

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 function plot

width

width (in inches) of the graphics device opened

height

height (in inches) of the graphics device opened

withSweave

logical: if TRUE (for working with Sweave) no extra device is opened and height/width are not set

mfColRow

shall default partition in panels be used — defaults to TRUE

n.CI

numeric; number of points to be used for confidence interval

col.IdL

color for the identity line

lty.IdL

line type for the identity line

lwd.IdL

line width for the identity line

alpha.CI

confidence level

exact.pCI

logical; shall pointwise CIs be determined with exact Binomial distribution?

exact.sCI

logical; shall simultaneous CIs be determined with exact kolmogorov distribution?

nosym.pCI

logical; shall we use (shortest) asymmetric CIs?

col.pCI

color for the pointwise CI

lty.pCI

line type for the pointwise CI

lwd.pCI

line width for the pointwise CI

pch.pCI

symbol for points (for discrete mass points) in pointwise CI

cex.pCI

magnification factor for points (for discrete mass points) in pointwise CI

col.sCI

color for the simultaneous CI

lty.sCI

line type for the simultaneous CI

lwd.sCI

line width for the simultaneous CI

pch.sCI

symbol for points (for discrete mass points) in simultaneous CI

cex.sCI

magnification factor for points (for discrete mass points) in simultaneous CI

cex.pch

magnification factor for the plotted symbols

col.pch

color for the plotted symbols

jit.fac

jittering factor used for discrete distributions

check.NotInSupport

logical; shall we check if all x-quantiles lie in support(y)?

col.NotInSupport

logical; if preceding check TRUE color of x-quantiles if not in support(y)

with.legend

logical; shall a legend be plotted?

legend.bg

background color for the legend

legend.pos

position for the legend

legend.cex

magnification factor for the legend

legend.pref

character to be prepended to legend text

legend.postf

character to be appended to legend text

legend.alpha

nominal coverage probability

debug

logical; if TRUE additional output to debug confidence bounds.

withSubst

logical; if TRUE (default) pattern substitution for titles and lables is used; otherwise no substitution is used.

Details

qqplot

signature(x = "ANY", y = "ANY"): function qqplot from package stats.

qqplot

signature(x = "UnivariateDistribution", y = "UnivariateDistribution"): produces a QQ plot for two univariate distributions.

Value

A list of elements containing the information needed to compute the respective QQ plot, in particular it extends the elements of the return value of function qqplot from package stats, i.e., a list with components x and y for x and y coordinates of the plotted points; more specifically it contains

x

The x coordinates of the points that were/would be plotted

y

The corresponding quantiles of the second distribution, including NAs.

crit

A matrix with the lower and upper confidence bounds (computed by qqbounds).

err

logical vector of length 2.

(elements crit and err are taken from the return value(s) of qqbounds). The return value allows to recover all information used to produce the plot for later use in enhanced graphics (e.g. with ggplot).

Author(s)

Peter Ruckdeschel [email protected]

References

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

See Also

qqplot from package stats – the standard QQ plot function and qqbounds, used by qqplot to produce confidence intervals.

Examples

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qqplot(Norm(15,sqrt(30)), Chisq(df=15))
## some discrete Distributions:
P <- Pois(5)
B <- Binom(size=2000,prob=5/2000)
qqplot(B,P)
## Not run: 
## takes too much time for R CMD check --as-cran
qqplot(B,P, nosym.pCI=TRUE)

## End(Not run)
## some Lebesgue-Decomposed distributions:
mylist <- UnivarLebDecDistribution(discretePart=Binom(3,.3), acPart=Norm(2,2),
               acWeight=11/20)
mylist2 <- mylist+0.1
qqplot(mylist,mylist2)
qqplot(mylist,mylist2,exact.pCI=FALSE,exact.sCI=FALSE)
## Not run: 
## takes too much time for R CMD check --as-cran
qqplot(mylist,mylist2,nosym.pCI=TRUE)
## some ac. distribution with a gap
mylist3 <- UnivarMixingDistribution(Unif(0,0.3),Unif(0.6,1),mixCoeff=c(0.8,0.2))
gaps(mylist3)
mylist4 <- UnivarMixingDistribution(Unif(0,0.3),Unif(0.6,1),mixCoeff=c(0.6,0.4))
qqplot(mylist3,mylist4)
qqplot(mylist3,mylist4,nosym.pCI=TRUE)

## End(Not run)

distr documentation built on July 9, 2018, 3 a.m.