qqplot.das: QQ plot

In StatDA: Statistical Analysis for Environmental Data

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.

Value

No return value, creates a plot.

Author(s)

Peter Filzmoser <[e-mail]> http://cstat.tuwien.ac.at/filz/

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

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)

StatDA documentation built on June 7, 2023, 6:26 p.m.