qqPlot | R Documentation |
Plots empirical quantiles of a variable, or of studentized residuals from
a linear model, against theoretical quantiles of a comparison distribution. Includes
options not available in the qqnorm
function.
qqPlot(x, ...)
qqp(...)
## Default S3 method:
qqPlot(x, distribution="norm", groups, layout,
ylim=range(x, na.rm=TRUE), ylab=deparse(substitute(x)),
xlab=paste(distribution, "quantiles"), glab=deparse(substitute(groups)),
main=NULL, las=par("las"),
envelope=TRUE, col=carPalette()[1], col.lines=carPalette()[2],
lwd=2, pch=1, cex=par("cex"),
line=c("quartiles", "robust", "none"), id=TRUE, grid=TRUE, ...)
## S3 method for class 'formula'
qqPlot(formula, data, subset, id=TRUE, ylab, glab, ...)
## S3 method for class 'lm'
qqPlot(x, xlab=paste(distribution, "Quantiles"),
ylab=paste("Studentized Residuals(",
deparse(substitute(x)), ")", sep=""),
main=NULL, distribution=c("t", "norm"),
line=c("robust", "quartiles", "none"), las=par("las"),
simulate=TRUE, envelope=TRUE, reps=100,
col=carPalette()[1], col.lines=carPalette()[2], lwd=2, pch=1, cex=par("cex"),
id=TRUE, grid=TRUE, ...)
x |
vector of numeric values or |
distribution |
root name of comparison distribution – e.g., |
groups |
an optional factor; if specified, a QQ plot will be drawn for |
layout |
a 2-vector with the number of rows and columns for plotting by
groups – for example |
formula |
one-sided formula specifying a single variable to be plotted or a two-sided formula of
the form |
data |
optional data frame within which to evaluage the formula. |
subset |
optional subset expression to select cases to plot. |
ylim |
limits for vertical axis; defaults to the range of |
ylab |
label for vertical (empirical quantiles) axis. |
xlab |
label for horizontal (comparison quantiles) axis. |
glab |
label for the grouping variable. |
main |
label for plot. |
envelope |
|
las |
if |
col |
color for points; the default is the first entry
in the current car palette (see |
col.lines |
color for lines; the default is the second entry in the current car palette. |
pch |
plotting character for points; default is |
cex |
factor for expanding the size of plotted symbols; the default is
|
id |
controls point identification; if |
lwd |
line width; default is |
line |
|
simulate |
if |
reps |
integer; number of bootstrap replications for confidence envelope. |
... |
arguments such as |
grid |
If TRUE, the default, a light-gray background grid is put on the graph |
Draws theoretical quantile-comparison plots for variables and for studentized residuals from a linear model. A comparison line is drawn on the plot either through the quartiles of the two distributions, or by robust regression.
Any distribution for which quantile and
density functions exist in R (with prefixes q
and d
, respectively) may be used.
When plotting a vector, the confidence envelope is based on the SEs of the order statistics
of an independent random sample from the comparison distribution (see Fox, 2016).
Studentized residuals from linear models are plotted against the appropriate t-distribution with a point-wise
confidence envelope computed by default by a parametric bootstrap,
as described by Atkinson (1985).
The function qqp
is an abbreviation for qqPlot
.
The envelope
argument can take a list with the following named elements; if an element is missing, then the default value is used:
level
confidence level (default 0.95
).
style
one of "filled"
(the default), "lines"
, or "none"
.
col
color (default is the value of col.lines
).
alpha
transparency/opacity of a filled confidence envelope, a number between 0 and 1 (default 0.15
).
border
controls whether a border is drawn around a filled confidence envelope (default TRUE
).
These functions return the labels of identified points, unless a grouping factor is employed,
in which case NULL
is returned invisibly.
John Fox jfox@mcmaster.ca
Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.
Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.
Atkinson, A. C. (1985) Plots, Transformations, and Regression. Oxford.
qqplot
, qqnorm
,
qqline
, showLabels
x<-rchisq(100, df=2)
qqPlot(x)
qqPlot(x, dist="chisq", df=2, envelope=list(style="lines"))
qqPlot(~ income, data=Prestige, subset = type == "prof")
qqPlot(income ~ type, data=Prestige, layout=c(1, 3))
qqPlot(lm(prestige ~ income + education + type, data=Duncan),
envelope=.99)
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