zoomStar {symbolicDA}

zoom star chart for symbolic data

Description

plot in a form of zoom star chart for symbolic object described by interval-valued, multivalued and modal variables

Usage

zoomStar(table.Symbolic, j, variableSelection=NULL, offset=0.2, 
firstTick=0.2, labelCex=.8, labelOffset=.7, tickLength=.3, histWidth=0.04, 
histHeight=2, rotateLabels=TRUE, variableCex=NULL)

Arguments

table.Symbolic

symbolic data table

j

symbolic object number in symbolic data table used to create the chart

variableSelection

numbers of symbolic variables describing symbolic object used to create the chart, if NULL all variables are used

offset

relational offset of chart (margin size)

firstTick

place of first tick (relational to lenght of axis)

labelCex

labels cex parameter of labels

labelOffset

relational offset of labels

tickLength

relational length of single tick of axis

histWidth

histogram (for modal variables) relational width

histHeight

histogram (for modal variables) relational heigth

rotateLabels

if TRUE labels are rotated due to rotation of axes

variableCex

cex parameter of names of variables

Value

zoom star chart for selected symbolic object in which each axis represents a symbolic variable. Depending on the type of symbolic variable their implementations are presented as:

a) rectangle - interval range of interval-valued variable),

b) circles - categories of multinominal (or multinominal with weights) variable from among coloured circles means categories of the variable observed for the selected symbolic object

bar chart - additional chart for multinominal with weights variable in which each bar represents a weight (percentage share) of a category of the variable

Author(s)

Andrzej Dudek [e-mail], Justyna Wilk [e-mail] Department of Econometrics and Computer Science, Wroclaw University of Economics, Poland http://keii.ue.wroc.pl/symbolicDA/

References

Bock, H.H., Diday, E. (eds.) (2000), Analysis of symbolic data. Explanatory methods for extracting statistical information from complex data, Springer-Verlag, Berlin.

Diday, E., Noirhomme-Fraiture, M. (eds.) (2008), Symbolic Data Analysis with SODAS Software, John Wiley & Sons, Chichester.

See Also

plotInterval in clusterSim

Examples

# LONG RUNNING - UNCOMMENT TO RUN
# Example 1
#data("cars",package="symbolicDA")
#sdt<-cars
#zoomStar(sdt, j=12)

# Example 2
#data("cars",package="symbolicDA")
#sdt<-cars
#variables<-as.matrix(sdt$variables)
#indivN<-as.matrix(sdt$indivN)
#dist<-as.matrix(dist_SDA(sdt))
#classes<-DClust(dist, cl=5, iter=100)
#for(i in 1:max(classes)){
  #getOption("device")()  
  #zoomStar(sdt, .medoid2(dist, classes, i))}