cparcoord: Enhanced parallel coordinate plot

In gclus: Clustering Graphics

Description

This function draws a parallel coordinate plot of data. Variables may be reordered and panels colored in the display. It is a modified version of parcoord {MASS}.

Usage

cparcoord(data, order = NULL, panel.colors = NULL, col = 1, lty = 1, 
horizontal = FALSE, mar = NULL, ...)

Arguments

data	a numeric matrix
order	the order of variables. Default is the order in data.
panel.colors	either a vector or a matrix of panel colors. If a vector is supplied, the ith color is used for the ith panel. If a matrix, dimensions should match those of the variables. Diagonal entries are ignored.
col	a vector of colours, recycled as necessary for each observation.
lty	a vector of line types, recycled as necessary for each observation.
horizontal	If TRUE, orientation is horizontal.
mar	margin parameters, passed to par.
...	graphics parameters which are passed to matplot.

Details

If panel.colors is a matrix and order is supplied, panel.colors is reordered.

Author(s)

Catherine B. Hurley

References

Hurley, Catherine B. “Clustering Visualisations of Multidimensional Data”, Journal of Computational and Graphical Statistics, vol. 13, (4), pp 788-806, 2004.

See Also

cpairs, parcoord, dmat.color, colpairs, order.endlink.

Examples

data(state)
state.m <- colpairs(state.x77, 
function(x,y)  cor.test(x,y,"two.sided","kendall")$estimate, diag=1)
# OR, Works only in R1.8,  state.m <-cor(state.x77,method="kendall")  


state.col <- dmat.color(state.m)

cparcoord(state.x77, panel.color= state.col)
# Get rid of the panels with lots of line crossings (yellow) by reordering:
cparcoord(state.x77, order.endlink(state.m), state.col)

# To get rid of the panels with lots of long line segments:
#  use a different panel merit measure- pclen:

mins <- apply(state.x77,2,min)
ranges <- apply(state.x77,2,max) - mins
state.m <- -colpairs(scale(state.x77,mins,ranges), pclen)
cparcoord(state.x77, order.endlink(state.m), dmat.color(state.m))

gclus documentation built on May 2, 2019, 5:08 a.m.