R: Combines the results of appplying an index to each group of...

partition.crit {gclus} | R Documentation

## Combines the results of appplying an index to each group of observations

### Description

Applies the function `gfun` to each group of x and y values and combines the results using the function `cfun`

### Usage

    partition.crit(x, y, groups, gfun = gave, cfun = sum, ...)

### Arguments

`x` | is a numeric vector.
`y` | is a numeric vector.
`groups` | is a vector of group memberships.
`gfun` | is applied to the `x` and `y` data in each group.
`cfun` | combines the values returned by `gfun`.
`...` | arguements are passed to `gfun`.

### Details

The function `gfun` is applied to each group of `x` and `y` values. The function `cfun` is applied to the vector or matrix of `gfun` results.

### Value

The result of applying `cfun`.

### Author(s)

Catherine B. Hurley

### References

See Gordon, A. D. (1999). Classification. Second Edition. London: Chapman and Hall / CRC

### See Also

`gave`, `colpairs`, `order.single`

### Examples

    x <- runif(20)
    y <- runif(20)
    g <- rep(c("a","b"),10)

    partition.crit(x,y,g)

    data(bank)
    # m is a homogeneity measure of each pairwise variable plot
    m <- -colpairs(scale(bank[,-1]), partition.crit,gfun=gave,groups=bank[,1])

    # Color panels by level of m and reorder variables so that
    # pairs with high m are near the diagonal. Panels shown
    # in pink have the highest amount of group homogeneity, as measured by
    # gave.
    cpairs(bank[,-1],order=order.single(m), panel.colors=dmat.color(m),
    gap=.3,col=c("purple","black")[bank[,"Status"]+1],
    pch=c(5,3)[bank[,"Status"]+1])

    # Try  a different measure
    m <- -colpairs(scale(bank[,-1]), partition.crit,gfun=diameter,groups=bank[,1])

    cpairs(bank[,-1],order=order.single(m), panel.colors=dmat.color(m),
    gap=.3,col=c("purple","black")[bank[,"Status"]+1],
    pch=c(5,3)[bank[,"Status"]+1])

    # Result is the same, in this case.

[Package gclus version 1.3.1 Index]