StatDA (version 1.7.4)

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", add.plot=FALSE,xlim=NULL,ylim=NULL,...)

Arguments

x

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

add.plot

if TRUE the new plot is added to an old one

xlim

the range for the x-axis

ylim

the range for the y-axis

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.

See Also

par

Examples

Run this code
# NOT RUN {
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)
# }

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