qqPlot {car} | R Documentation |
Plots empirical quantiles of a variable, or of studentized residuals from a linear model, against theoretical quantiles of a comparison distribution.
qqPlot(x, ...) qqp(...) ## Default S3 method: qqPlot(x, distribution="norm", ylab=deparse(substitute(x)), xlab=paste(distribution, "quantiles"), main=NULL, las=par("las"), envelope=.95, col=palette()[1], col.lines=palette()[2], lwd=2, pch=1, cex=par("cex"), line=c("quartiles", "robust", "none"), labels = if(!is.null(names(x))) names(x) else seq(along=x), id.method = "y", id.n =if(id.method[1]=="identify") Inf else 0, id.cex=1, id.col=palette()[1], grid=TRUE, ...) ## 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=.95, reps=100, col=palette()[1], col.lines=palette()[2], lwd=2, pch=1, cex=par("cex"), labels, id.method = "y", id.n = if(id.method[1]=="identify") Inf else 0, id.cex=1, id.col=palette()[1], grid=TRUE, ...)
x |
vector of numeric values or lm object. |
distribution |
root name of comparison distribution – e.g., "norm" for the
normal distribution; t for the t-distribution. |
ylab |
label for vertical (empirical quantiles) axis. |
xlab |
label for horizontal (comparison quantiles) axis. |
main |
label for plot. |
envelope |
confidence level for point-wise confidence envelope, or
FALSE for no envelope. |
las |
if 0 , ticks labels are drawn parallel to the
axis; set to 1 for horizontal labels (see par ). |
col |
color for points; the default is the first entry
in the current color palette (see palette
and par ). |
col.lines |
color for lines; the default is the second entry in the current color palette. |
pch |
plotting character for points; default is 1
(a circle, see par ). |
cex |
factor for expanding the size of plotted symbols; the default is
1 . |
labels |
vector of text strings to be used to identify points, defaults to
names(x) or observation numbers if names(x) is NULL . |
id.method |
point identification method. The default
id.method="y"
will identify the id.n points with the largest value of
abs(y-mean(y)) . See showLabels for other options. |
id.n |
number of points labeled. If id.n=0 , the default, no
point identification. |
id.cex |
set size of the text for point labels; the default is cex (which is typically 1 ). |
id.col |
color for the point labels. |
lwd |
line width; default is 2 (see par ). |
line |
"quartiles" to pass a line through the quartile-pairs, or
"robust" for a robust-regression line; the latter uses the rlm
function in the MASS package. Specifying line = "none" suppresses the line. |
simulate |
if TRUE calculate confidence envelope by parametric bootstrap;
for lm object only. The method is due to Atkinson (1985). |
reps |
integer; number of bootstrap replications for confidence envelope. |
... |
arguments such as df to be passed to the appropriate quantile function. |
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.
Studentized residuals from linear models are plotted against the appropriate t-distribution.
The function qqp
is an abbreviation for qqPlot
.
These functions return the labels of identified points.
John Fox jfox@mcmaster.ca
Fox, J. (2008) Applied Regression Analysis and Generalized Linear Models, Second Edition. Sage.
Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second 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) qqPlot(lm(prestige ~ income + education + type, data=Duncan), envelope=.99)