R: Profile smoothness measures

pclen {gclus} | R Documentation

## Profile smoothness measures

### Description

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

### Usage

    pclen(x, y)
    pcglen(x, y)

### Arguments

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

### Details

`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.

### Value

The panel measure is returned.

### 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

`cparcoord`, `colpairs`, `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)

[Package gclus version 1.3.1 Index]