plotting: Plotting BPAs
In ipptoolbox: IPP Toolbox

Description Usage Arguments Details Value Author(s) Examples

Various routines to visualize BPAs

dscdf(x, xrange = NULL, col = c(3, 4), ..., newplot = TRUE)
dsqqplot(ds, sample, points = FALSE)
dsbel(x)
dspl(x)

`x`	BPA to plot
`xrange`	Optional: xrange=c(1,5) limits the x-axis to [1,5]
`col`	Optional: col = c(3,4) defines the colors of the Bel and the Pl line.
`...`	Optional: additional parameters passed to the plot routine (except linewidth, linetype and color)
`newplot`	Optional: Create a new plot or draw lines onto an existing plot.
`sample`	set of data values, e. g. c(1.5,2,3.5)
`ds`	BPA for qq plot resembling sample
`points`	Optional, points=TRUE: plot the sample values as points + line, otherwise only a straight line.

dscdf: Plots Bel([-Inf,x]) and Pl([-Inf,x]). These functions bound all CDFs.
dsqqplot: Plots a quantile-quantile plot between data and a BPA.
dsbel: Returns Bel([-Inf,x]), e. g. for own plotting routines.
dspl: Returns Pl([-Inf,x]), e. g. for own plotting routines.

The function dscdf plots Bel([-Inf,x]) and Pl([-Inf,x]), the bounds on all CDFs. Arbitrary graphics parameters can be passed to dscdf. dsqqplot plots a quantile-quantile plot between data and a BPA. dsbel and dspl return the function Bel([-Inf,x])/ Pl([-Inf,x]) as a set of (x,y)-type points, e. g. for own plotting routines.

The example generates a BPA. It plots the BPA first without, then with additional parameters. Finally it uses the functions dsbel and dspl for plotting points into the diagram. Then it generates a BPA from a normal pbox with imprecise standard deviation. It tests with a QQ plot, if the function fits well to a random sample from N(0,1).

dscdf returns the x and y coordinates of the plotted lines for further use.

Philipp Limbourg <p.limbourg@uni-due.de>

print("Plot new BPA")
a=dsstruct(rbind(c(1,2,0.3),c(1.5,5,0.5),c(4,6,0.2)))
dscdf(a)

dscdf(a,xrange=c(0,7),xlab="Important parameter")
print("Bel([-Inf,x])")
bel=dsbel(a)
print("Pl([-Inf,x])")
pl=dspl(a)
points(pl,lwd=5,col='red')
points(bel,lwd=5,col='pink')

print("See if a pbox from N(0,[0.5,1.5]) fits data from N(0,1)")
data=rnorm(100,0,1)
pbox=dsodf(qnorm,1000,0,dsstruct(c(0.5,1.5,1)))
print("Plot pbox")
dscdf(pbox)

print("qq plot")
dsqqplot(pbox,data)