plot.mixer {mixer} | R Documentation |
plot.mixer
can display five kinds of figure: Integrated Classification
Criterion curve, the adjacency matrix map, the degree distribution histogram, the
connectivity matrix graph and the adjacency matrix graph. By default the four
first plots are displayed.
## S3 method for class 'mixer': plot(x, q=NULL, frame=1:4, classes=NULL, quantile.val=0.1, ...)
x |
a mixer object (output of the mixer function). |
q |
the q-class model to display. By default, the q
is set to the value which maximizes the criterion (see frame 1). |
frame |
a vector of frame numbers to display (5 kinds of plots, see details section for more). |
classes |
an external classification used for frame 4 (pie chart):
vector as factor of node elements (the number of external
class levels corresponds to the number of levels).
|
quantile.val |
filters the connectivity matrix values
(Pis) in frame 4. Display the upper part (specified by
quantile.val ) of the distribution.
|
... |
further graphical arguments. |
Frame values:
mixer
).
q
.
alphas
, Pis
).
q
. The thickest edges
identify the highest values of the connectivity probabilities
and the largest nodes point out the most populated classes.
Providing external classes (see classes argument) each node displays a pie chart pointing out the classification relevance.
C. Ambroise, G. Grasseau
# # Simple example : display the 4 frames for the best class number estimation # g <- graph.affiliation(n=100,c(1/3,1/3,1/3),0.8,0.2) xout <- mixer(g$x,qmin=2,qmax=6) ## Not run: plot(xout) # # Display the same for 4 classes with no filtering # ## Not run: plot(xout, q=4, quantile.val=0) # # Display a pie chart for 4 classes # data(blog) xout <- mixer(x=blog$links,qmin=2,qmax=12) # Unconnected nodes have been removed by mixer. # xout$map contains the mapping from connected nodes to the whole set ext.classes <- blog$politicalParty[ xout$map ] ## Not run: plot( xout, frame=4, classes=ext.classes )