gclus (version 1.3.2)

partition.crit: 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.

Value

The result of applying cfun.

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.

References

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

See Also

gave, colpairs, order.single

Examples

# NOT RUN {
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.

# }

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