cparcoord: Enhanced parallel coordinate plot

Description Usage Arguments Details Author(s) References See Also Examples

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

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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

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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.