ockc {ockc} | R Documentation |
Order Contrained Solutions in k-Means Clustering
Description
Calculates an order constrained clustering solution (default k-means) on a data matrix.
Usage
ockc(x, k, family = kccaFamily("kmeans"), order = NULL, control = NULL,
save.data = FALSE, multicore = FALSE, ...)
Arguments
x |
A numeric matrix of data. |
k |
An integer vector of number of clusters. For each element of k a clustering solution is computed (reusage of intermediate results makes this more efficient than individual calls of ockc). |
family |
Object of class |
order |
Order restriction of |
control |
An object of class |
save.data |
Save a copy of |
multicore |
Use parallelization, if available. For examples and additional
documentation see |
... |
Additional options for |
Author(s)
Sebastian Krey, Friedrich Leisch, Sebastian Hoffmeister
References
Steinley, D. and Hubert, L. (2008). Order-Constrained Solutions in K-Means Clustering: Even Better Than Being Globally Optimal. Psychometrika, 73 (4), pp. 647-664.
See Also
Examples
x <- rbind(cbind(rnorm(10, mean=0), rnorm(10, mean=0,), rnorm(10, mean=0)),
cbind(rnorm(10, mean=10), rnorm(10, mean=10), rnorm(10, mean=0)),
cbind(rnorm(10, mean=10), rnorm(10, mean=0), rnorm(10, mean=10)),
cbind(rnorm(10, mean=10), rnorm(10, mean=10), rnorm(10, mean=10))
)
res <- ockc(x, k=4, nboot=4, order=c(1:10, 21:40, 11:20))
res