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 |
cfun |
combines the values returned by |
... |
arguements are passed to |
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
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 1.3.2 Index]