\name{pclen} \alias{pclen} \alias{pcglen} %- Also NEED an '\alias' for EACH other topic documented here. \title{ Profile smoothness measures } \description{ Computes measures of profile smoothness of 2-d data, where \code{x} and \code{y} give the object coordinates. } \usage{ pclen(x, y) pcglen(x, y) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{x}{is a numeric vector. } \item{y}{is a numeric vector. } } \details{ \code{pclen} computes the total line length in a parallel coordinate plot of x and y. \code{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. } \value{The panel measure is returned. } \references{Hurley, Catherine B. \dQuote{Clustering Visualisations of Multidimensional Data}, Journal of Computational and Graphical Statistics, vol. 13, (4), pp 788-806, 2004. } \author{ Catherine B. Hurley } %\note{ ~~further notes~~ } \seealso{\code{\link{cparcoord}}, \code{\link{colpairs}}, \code{\link{order.endlink}}.} \examples{ 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) } \keyword{hplot} \keyword{multivariate}