qqplot {distrMod} | R Documentation |
Methods for Function qqplot in Package ‘distrMod’
Description
We generalize function qqplot
from package stats to
be applicable to distribution and probability model objects, as well as
to estimate objects. In this context,
qqplot
produces a QQ plot of data (argument x
) against
a (model) distribution. If the second argument is of class 'Estimate'
,
qqplot
looks at the estimate.call
-slot and checks whether
it can use an argument ParamFamily
to conclude on the model
distribution. Graphical parameters may be given as arguments to
qqplot
.
In all title and 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
qqplot(x, y, ...)
## S4 method for signature 'ANY,UnivariateDistribution'
qqplot(x,y,
n = length(x), withIdLine = TRUE,
withConf = TRUE, withConf.pw = withConf, withConf.sim = withConf,
plot.it = TRUE, datax = FALSE, xlab = deparse(substitute(x)),
ylab = deparse(substitute(y)),
..., width = 10, height = 5.5, withSweave = getdistrOption("withSweave"),
mfColRow = TRUE, n.CI = n, with.lab = FALSE, lab.pts = NULL, which.lbs = NULL,
which.Order = NULL, which.nonlbs = NULL, attr.pre = FALSE, order.traf = NULL,
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"), added.points.CI = TRUE,
cex.pch = par("cex"), col.pch = par("col"),
cex.pts = 1, col.pts = par("col"), pch.pts = 19,
cex.npts = 1, col.npts = grey(.5), pch.npts = 20,
cex.lbs = par("cex"), col.lbs = par("col"), adj.lbs = par("adj"),
alpha.trsp = NA, jit.fac = 0, jit.tol = .Machine$double.eps,
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,ProbFamily'
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)), ...)
## S4 method for signature 'ANY,Estimate'
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)), ...)
Arguments
x |
data to be checked for compatibility with distribution/model |
y |
object of class |
n |
numeric; assumed sample size (by default length of |
withIdLine |
logical; shall line |
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
|
datax |
logical; shall data be plotted on x-axis? |
xlab |
x-label |
ylab |
y-label |
... |
further parameters for method |
width |
width (in inches) of the graphics device opened |
height |
height (in inches) of the graphics device opened |
withSweave |
logical: if |
mfColRow |
shall default partition in panels be used — defaults to |
n.CI |
numeric; number of points to be used for confidence interval |
with.lab |
logical; shall observation labels be plotted in? |
lab.pts |
character or |
attr.pre |
logical; do graphical attributes for plotted data refer
to indices prior ( |
which.lbs |
integer or |
which.Order |
integer or |
which.nonlbs |
indices of the observations which should be plotted but
not labelled; either an integer vector with the indices of the observations
to be plotted into graph or |
order.traf |
function or |
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 |
added.points.CI |
logical; should CIs be plotted through additional points (and not only through data points)? |
cex.pch |
magnification factor for the plotted symbols (for backward
compatibility); it is ignored once |
col.pch |
color for the plotted symbols (for backward compatibility); it is
ignored once |
cex.pts |
size of the points of the second argument plotted, can be a vector;
if argument |
col.pts |
color of the points of the second argument plotted, can
be a vector as in |
pch.pts |
symbol of the points of the second argument plotted, can
be a vector as in |
col.npts |
color of the non-labelled points of the |
pch.npts |
symbol of the non-labelled points of the |
cex.npts |
size of the non-labelled points of the |
cex.lbs |
magnification factor for the plotted observation labels |
col.lbs |
color for the plotted observation labels |
adj.lbs |
adj parameter for the plotted observation labels |
alpha.trsp |
alpha transparency to be added ex post to colors
|
jit.fac |
jittering factor used for discrete distributions. |
jit.tol |
threshold for jittering: if distance between points is smaller
than |
check.NotInSupport |
logical; shall we check if all |
col.NotInSupport |
logical; if preceding check |
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 |
withSubst |
logical; if |
Details
- qqplot
signature(x = "ANY", y = "UnivariateDistribution")
: produces a QQ plot of a datasetx
against the theoretical quantiles of distributiony
.- qqplot
signature(x = "ANY", y = "ProbFamily")
: produces a QQ plot of a datasetx
against the theoretical quantiles of the model distribution of modely
. Passed through the...
argument, all arguments valid forsignature(x = "ANY", y = "UnivariateDistribution")
are also valid for this signature.- qqplot
signature(x = "ANY", y = "Estimate")
: produces a QQ plot of a datasetx
against the theoretical quantiles of the model distribution of the model that can be reconstructed from the estimatory
; more specifically, it tries to get hand at the argument'ParamFamily'
of the esimator's call; if this is available, internally this model is shifted to the estimated parameter by a call tomodifyModel
, and then this shifted model is used in a call to the(x = "ANY", y = "UnivariateDistribution")
-method. Passed through the...
argument, all arguments valid forsignature(x = "ANY", y = "UnivariateDistribution")
are also valid for this signature.
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 |
crit |
A matrix with the lower and upper confidence bounds
(computed by |
err |
logical vector of length 2. |
(elements crit
and err
are taken from the return
value(s) of qqbounds
).
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.
See Also
qqplot
from package stats – the standard QQ plot
function, qqplot
from package distr for
comparisons of distributions, and
qqbounds
, used by qqplot
to produce confidence
intervals.
Examples
set.seed(123)
x <- rnorm(40,mean=15,sd=30)
qqplot(x, Chisq(df=15))
NF <- NormLocationScaleFamily(mean=15, sd=30)
qqplot(x, NF, with.lab=TRUE, which.Order=1:5, cex.lbs=1.3)
mlE <- MLEstimator(x, NF)
qqplot(x, mlE)