pclen: Profile smoothness measures
In gclus: Clustering Graphics

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

Computes measures of profile smoothness of 2-d data, where x and y give the object coordinates.

1 2	pclen(x, y) pcglen(x, y)

`x`	is a numeric vector.
`y`	is a numeric vector.

pclen computes the total line length in a parallel coordinate plot of x and y.

pcglen computes the average (per object) line length in a parallel coordinate plot where all pairs of objects are connected.

Usually, the data is standardized prior to using these functions.

The panel measure is returned.

Catherine B. Hurley

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

cparcoord, colpairs, order.endlink.

x <- runif(20)
y <- runif(20)
pclen(x,y)


data(state)
mins <- apply(state.x77,2,min)
ranges <- apply(state.x77,2,max) - mins
state.m <- -colpairs(scale(state.x77,mins,ranges), pclen)
state.col <- dmat.color(state.m)
cparcoord(state.x77, panel.color= state.col)
# Get rid of the panels with long line segments (yellow) by reordering:
cparcoord(state.x77, order.endlink(state.m), state.col)