qqplot.das: QQ plot

Description

A QQ (Quantile-Quantile) plot is produced.

Usage

qqplot.das(x, distribution = "norm", ylab = deparse(substitute(x)), xlab = paste(distribution, "quantiles"), main = "", las = par("las"), datax = FALSE, envelope = 0.95, labels = FALSE, col = palette()[2], lwd = 2, pch = 1, line = c("quartiles", "robust", "none"), cex = 1, xaxt = "s", ...)

Arguments

numeric vector

distribution

name of the comparison distribution

ylab

label for the y axis (empirical quantiles)

xlab

label for the x axis (comparison quantiles)

main

title for the plot

las

if 0, ticks labels are drawn parallel to the axis

datax

if TRUE, x and y axis are exchanged

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

col, lwd, pch, cex, xaxt

graphical parameter, see par

line

"quartiles" to pass a line through the quartile-pairs, or "robust" for a robust-regression line. "none" suppresses the line

...

further arguments for the probability function

Details

The probability of the input data is computed and with this result the quantiles of the comparison distribution are calculated. If line="quartiles" a line based on quartiles is plotted and if line="robust" a robust LM model is calculated.

References

C. Reimann, P. Filzmoser, R.G. Garrett, and R. Dutter: Statistical Data Analysis Explained. Applied Environmental Statistics with R. John Wiley and Sons, Chichester, 2008.

Examples

Run this code

data(AuNEW)
qqplot.das(AuNEW,distribution="lnorm",col=1,envelope=FALSE,datax=TRUE,ylab="Au",
xlab="Quantiles of lognormal distribution", main="",line="none",pch=3,cex=0.7)