qqfun {gap} | R Documentation |
Plots empirical quantiles of a variable against theoretical quantiles of a comparison distribution.
qqfun(x, distribution="norm", ylab=deparse(substitute(x)), xlab=paste(distribution, "quantiles"), main=NULL, las=par("las"), envelope=.95, labels=FALSE, col=palette()[4], lcol=palette()[2], xlim=NULL, ylim=NULL, lwd=1, pch=1, bg=palette()[4], cex=.4, line=c("quartiles", "robust", "none"), ...)
x |
vector of numeric values. |
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. |
labels |
vector of point labels for interactive point identification,
or FALSE for no labels. |
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 fourth entry
in the current color palette (see palette
and par ). |
lcol |
color for lines; the default is the second entry as above. |
xlim |
the x limits (x1, x2) of the plot. Note that x1 > x2 is allowed and leads to a reversed axis. |
ylim |
the y limits of the plot |
pch |
plotting character for points; default is 1
(a circle, see par ). |
bg |
background color of points |
cex |
factor for expanding the size of plotted symbols; the default is
.4 . |
lwd |
line width; default is 1 (see par ).
Confidence envelopes are drawn at half this line width. |
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. |
... |
arguments such as df to be passed to the appropriate quantile function. |
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 are plotted against the appropriate t-distribution.
This is adapted from qq.plot
with different values for points and lines,
more options, more transparent code and examples in the current setting. Another similar but
sophisticated function is qqmath
.
NULL
. These functions are used only for their side effect (to make a graph).
John Fox, Jing Hua Zhao
Davison, A. C. (2003) Statistical Models. Cambridge University Press.
Leemis, L. M., J. T. Mcqueston (2008) Univariate distribution relationships. The American Statistician 62:45-53
qqplot
, qqnorm
, qqline
,
qqunif
, gcontrol2
## Not run: p <- runif(100) alpha <- 1/log(10) qqfun(p,dist="unif") qqfun(-log10(p),dist="exp",rate=alpha,pch=21) library(car) qq.plot(p,dist="unif") qq.plot(-log10(p),dist="exp",rate=alpha) library(lattice) qqmath(~ -log10(p), distribution = function(p) qexp(p,rate=alpha)) ## End(Not run)