StatDA (version 1.7.4)

qpplot.das: QP plot

Description

This function produces a QP (Quantile-Probability) plot of the data.

Usage

qpplot.das(x, qdist = qnorm, probs = NULL, logx = FALSE, cex.lab = 1,
xlab = NULL, ylab = "Probability [%]", line = TRUE, lwd = 2, pch = 3,
logfinetick = c(10), logfinelab = c(10), cex = 0.7, xlim = NULL,
ylim = NULL, gridy = TRUE, add.plot = FALSE, col = 1, ...)

Arguments

x

data

qdist

The probability function with which the data should be compared.

probs

The selected probabilities, see details

logx

if TRUE, then log scale on x-axis is used

cex.lab

The size of the label

xlab

title for x-axis

ylab

title for y-axis

line

if TRUE the line will be drawn

lwd

the width of the line

pch, cex, col

graphical parameter

logfinetick

how fine are the tick marks on log-scale on x-axis

logfinelab

how fine are the labels on log-scale on x-axis

xlim

the range for the x-axis

ylim

the range for the y-axis

gridy

if grid along y-axis should be drawn

add.plot

if TRUE the new plot is added to an old one

…

futher arguments for the probability function

Details

First the probability of the sorted input x is computed and than the selected quantiles are calculated and after that plot is produced. If probs=NULL then the 1%, 5%, 10%, 20%,...., 90%, 95% and 99% quantile is taken.

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

plot, par, plot.default

Examples

# NOT RUN {
data(AuNEW)
qpplot.das(AuNEW,qdist=qlnorm,xlab="Au",
ylab="Probabilities of lognormal distribution", pch=3,cex=0.7)
# }